# DCA (Dual Chunk Attention) — Evaluation Results

**Workstream:** T87.pD — Dual Chunk Attention for long-context prefill in the opencoti
llamafile fork (Gemma 4 26B-A4B 1M-context path on a single GPU, + Qwen2/3/3.5 portability).
**Patch:** `vendors/patches/llamafile/0078-dca.patch`.

> ⚠ **Absolute prefill tok/s in this doc are stale-low as of 2026-07-05 (#614):** the
> tinyblas-small-gemm fix (bug-2104) lifts Gemma-A4B MoE-router prefill substantially on
> TinyBLAS builds, so cells below understate the current binary; the DCA-on-vs-off *ratios*
> and all quality scores remain valid. The #614 checkpoint fixes (bug-2105/2107) do NOT
> affect these runs — the recipe here pins `--ctx-checkpoints 0`. Current cross-engine
> prefill: [`three-way-tps.md`](three-way-tps.md) §2026-07-05.
**Last updated:** 2026-06-18 (Thursday) — *added **§5 (KV-quant × DCA full-vocab PPL/KLD, #446)**:
teacher-forced KL-divergence resolves the turbo-DCA anomaly — turbo-DCA `real_frac=0` is **GENUINE**
(DCA f16-lift KLD monotone in tier bits: turbo8 0.002 → turbo2 0.65), and the DCA lift **beats** the
noDCA in-register turbo read (turbo2 in-register is degenerate: KLD 5.60 / PPL 1584 vs turbo2-DCA 0.65).
Scalar/asym matrix complete — best long-ctx KV recipe is high-precision-K + q4/turbo4-V (q8K/q4V &
t8K/t4V ≈ KLD 0.003–0.008, top 96–98%); the turbo2 noDCA degeneracy is K-side (t4K/t2V fine).
Earlier (2026-06-15 → 2026-07-13): the **RULER-VT 1M cell landed** (§1a) and is now **0.916** on the
current shipping binary — **the quality ladder is complete**. (History: originally 0.716 = server-crash
artifact; 0.876 = 2026-07-01 pre-fix 41+9-refix reconstruction; **0.916 = 2026-07-13 fixed-binary
`_dcaon_rerun`, clean n=50, 0 empties** — the current number. See §1a◇.) DCA-on holds the 0.96–0.98 VT
band 256k→512k, then softens *gently*: 768k **0.984**, 1M **0.916** (a mild −6.8 pp at 4× native,
`n_ctx_train`=256k) — no cliff. **Re-confirmed on the fresh 0121
binary (#654): all four DCA-on rungs now on the current engine — 256k 0.964 / 512k 0.996 / 768k 0.984 /
1M 0.916, n=50, 0 empties** (768k the last holdout, re-run 2026-07-13: 0.956→0.984). See the §1a note.
Earlier: MRCR n=50 re-run (§1b: 256k-off 0.1138 / 256k-on 0.1320 / 512k-on 0.1027); §4d (#635 decode
chunk-boundary gate). See `docs/DCA_HANDOFF.md` for the full patch hand-off (RCA, file inventory,
cross-arch risks).*

This doc collects **every DCA evaluation** we've run: long-context quality (RULER-VT + MRCR),
throughput (prefill/gen tps), memory footprint (VRAM), and correctness gates (multi-chunk
coherence, NIAH retrieval). Quality scores are read from the canonical `summary.json` `.score`;
throughput/VRAM from the llama-server logs (`timings`, KV/compute-buffer lines) and live `nvidia-smi`.

---

## 0. Hosts & methodology

Two hosts produced these numbers — **attribute every row to its host**, they are not comparable across GPUs:

| Host | GPU | VRAM | Role |
|------|-----|------|------|
| **bs2** (linode-blackswan-2) | 1× Blackwell-class | 97,887 MiB (~96 GB) | Long-context **quality ladder** (128e-F16, 256k–1M). Fits weights+KV up to 1M. |
| **solidpc** | 1× RTX 3090 | 24,576 MiB (~24 GB) | **Throughput** (3-arm gen-tps) + **correctness gates** (multi-chunk coherence, regression). Q4_K_M / quantized models only. |

- **Sampler:** greedy (`temperature 0`, `top_k 1`) everywhere — DCA is a serving-correctness feature, scores must be deterministic.
- **DCA recipe:** `--dca on --dca-chunk-size 8192` (so ctx/8192 = chunk count), `-fa on --parallel 1 --no-warmup --ctx-checkpoints 0`.
- **DCA-off above 256k = N/A:** full attention KV does not fit a single GPU past 256k; DCA is what makes those tiers reachable, so there is no off-arm to compare against. 256k is the only tier with both arms (the regression anchor).
- **Backend:** `omk_eval.py --backend llama` launching the opencoti DCA llamafile (`/srv/ml/opencoti-dca/bin/llamafile`) per cell, `--parallel 1 --replicas 1` (serial, one full-ctx slot).

### Models under test

| Short name | Arch | head_dim (DKQ) | Quant | Weights on disk | Notes |
|------------|------|----------------|-------|-----------------|-------|
| **128e-F16** | gemma4 (iSWA) | 512 | F16 GGUF | 50.5 GB (48,150 MiB in VRAM) | Clean unpruned 26B-A4B base. Ladder model. |
| gemma-4-26B-A4B-it-Q4_K_M | gemma4 (iSWA) | 512 | Q4_K_M | ~17.5 GB | solidpc 3-arm gen-tps model. |
| v7-coder-it (98e) | gemma4 (iSWA) | 512 | Q4_K_M | 13.2 GB | 98e pruned. **Reference only** — early upper-tier MRCR cells, superseded by 128e-F16 re-runs. |
| Qwen3.6-35B-A3B | qwen35moe | 256 | UD-IQ3_XXS | 13.2 GB | Qwen multi-chunk portability gate. |
| Qwen3-4B | qwen3 | 128 | Q4_K_M | 2.5 GB | Qwen multi-chunk portability gate. |
| Qwen3.6-27B-Omnimerge-v4 | qwen35 (hybrid, MTP) | 256 | Q4_K_M | 16.8 GB | MTP-with-Qwen capability + DCA multi-chunk gate (#622). |

---

## 1. Long-context quality ladder — 128e-F16 (bs2 Blackwell)

Single model, greedy, ±DCA. DCA-off N/A above 256k (won't fit). **Each bench has its own metric** —
RULER-VT = `string_match_all`, MRCR = `sequence_matcher_ratio` (fuzzy ratio, NOT pass@1). For MRCR,
**prefill/gen tps + VRAM + wall/req are the authoritative values from `summary.json` `scores`**
(`prefill_tok_s`/`gen_tok_s`/`vram_peak_mib`/`wall_s_median`); RULER-VT's `scores` block carries no
perf fields, so its tps are medians read from the per-cell `server.log`.

> ⚠️ **MRCR tiers are different synthetic bins, NOT a comparable column.** Each MRCR row draws its
> prompts from a distinct `mrcr_bin` (256k real / 512k / 768k_synth) with a different needle-count
> mix, so MRCR scores do **not** form a monotone "longer = lower" curve and must not be read as one.
> RULER-VT *is* a consistent metric across ctx, so its rows are comparable.

### 1a. RULER-VT (Variable Tracking, 50 samples) — `string_match_all`

**Model: `128e-F16`** (Gemma-4 26B-A4B, iSWA, head_dim 512, F16 GGUF — 48.2 GB weights; see §0
"Models under test"). **Note the VRAM column grows *sub-linearly* with ctx** (54.5 → 61.3 → 69 → 70 GB):
Gemma-4's iSWA means most layers are **local sliding-window** (KV capped at the window, *independent of
total ctx*) and only the minority **global** layers (just **2 KV heads** × head_dim 512) scale with ctx.
So 768k→1M (+262k tokens) enlarges only the global layers ≈ **+1 GB** — not the ~5 GB an all-global model
would add. That sliding-window KV is exactly what fits 1M (KV 20.8 GB) on a single 96 GB card.

| ctx | DCA | score | prefill tok/s | gen tok/s | VRAM | wall-clock | status |
|-----|-----|-------|---------------|-----------|------|------------|--------|
| 256k | off | **0.964** | 2275.6 (med, rerun) | 88.3 (med, rerun) | ~54.5 GB | 1h39m | done (#654 rerun) |
| 256k | on  | **0.964** | 2323.1 (med, rerun) | 87.0 (med, rerun) | ~54.5 GB | 1h40m | done (#654 rerun) |
| 512k | on  | **0.996** | 1752.1 (med, rerun) | 67.5 (med, rerun) | ~61.3 GB | 4h18m | done (#654 rerun) |
| 768k | on  | **0.984** | 1407.8 (med, rerun) | 55.2 (med, rerun) | ~67 GB | 8h02m | done (#654 rerun) |
| 1M   | on  | **0.916**◇ | 1175.6 (med, rerun) | 46.4 (med, rerun) | ~70 GB | 12h36m | done (#654 rerun) |

> **#654 re-run on the fresh 0121 binary CONFIRMS the ladder end-to-end** — DCA-on 256k **0.964**
> (was 0.960, 2026-07-12), 512k **0.996** (was 0.984, 2026-07-12), **768k 0.984** (was 0.956
> orig-binary; fresh rerun finished 2026-07-13 16:23 UTC, 8h02m), and **1M 0.916** (was 0.876,
> finished 2026-07-13 04:42 UTC, 12.6 h) — **all n=50 with 0 empties** (`fresh_empty=0`, no
> server-death artifact this run). The 1M rerun is the decisive one: a **fully-clean single-pass n=50**
> (not the 41-perfect + 9-refix reconstruction the 0.876 was) on the **post-bug-2118/2120/2121 shipping
> binary** lands **+4 pp higher at 0.916**, so 0.916 supersedes 0.876 as the true VT-1M ceiling and the
> gentle 768k→1M step is ~−6.8 pp (0.984→0.916), a soft slope not a cliff. The load-bearing conclusion (near-parity at 256k, band
> held 256k→512k, no cliff to 4× native) is unchanged and strengthened on the current engine. Results:
> `bs2:/srv/ml/rerun/vt-out/ruler_native_vt_{256,512}k,1024k_dcaon_rerun/`.
>
> **The rerun tps are ~2–3× the original run** (prefill 256k 747→2323, 512k 681→1752, 1M 577→1176;
> gen also up: 256k 84→87, 512k 65→68, 1M 44→46) — the shipping binary carries every prefill/decode fix
> landed since June (#554 DCA-prefill-cliff, #614 large-batch prefill, #620 bandwidth-bound quant, WS2
> turbo-V). The table's rows are all **current-binary rerun medians** — **every rung, DCA-on (256k / 512k /
> 768k / 1M) AND the 256k-off anchor, is now on the fresh binary.** 768k was the last DCA-on holdout (re-run
> 2026-07-13: 0.956→0.984, prefill 632→1408, gen 52→55, wall 17h44m→8h02m) and 256k-off was the last
> full-attention holdout (re-run 2026-07-13: 0.976→0.964, prefill 676→2276, gen 86→88, wall 5h28m→1h39m,
> n=50 `fresh_empty=0`). Wall-clock roughly halved across the board (1M 24 h → 12.6 h; 768k 17.7 h → 8.0 h;
> 256k-off 5.5 h → 1.6 h).

◇ **1M is 0.916 on the current shipping binary** (fixed-binary `_dcaon_rerun`, 2026-07-13, clean n=50
`fresh_empty=0`) — see the #654 note above; this supersedes the 0.876 below. The 0.876/0.716 history is
retained for provenance. **0.876 was the pre-fix reconstruction** (resolved 2026-07-01, a 41-perfect +
9-refix rebuild on the pre-bug-2118/2120 binary). The 0.716 was a **serving
artifact**: the first F16 server crashed after sample 40 (~24 h uptime), so samples 41–49 all returned
`gen-error: ConnectionError` (one RemoteDisconnected, then 8× Connection-refused) → 9 forced zeros
(`fresh_empty=9`). The 9 were re-run on a fresh server (cache-resume; the 41 good samples kept, only the 9
dead keys re-predicted, ~4.5 h) and all produced real completions → the re-scored n=50 cell is **0.876**
(`fresh_empty=0`, 35/50 perfect, 3 genuine zeros). Recompute over the pre-fix 50 (dead=0) reproduces 0.716
exactly and over the 41 then-served samples gives 0.873, so the 9 re-runs land right on the served
distribution — the crash, not 1M coherence, drove the apparent cliff.

DCA-on vs full attention at 256k, **both now on the fresh binary**: **0.964 vs 0.964 — exact parity**
(DCA is lossless at 256k within VT n=50 sample noise; the earlier −1.2 pp was a stale original-binary
full-attn 0.976). Speed is at parity too — DCA-on prefill 2323 / gen 87 vs DCA-off 2276 / gen 88 tok/s —
so DCA costs neither quality nor throughput at the native cap. This is the load-bearing quality result:
on a consistent metric, multi-chunk DCA preserves long-context tracking. At **512k** DCA-on holds at **0.996** — above both its own 256k point and the 256k
full-attention anchor (both 0.964), i.e. variable tracking does not degrade as context doubles past the
native cap (gen tps 67.5, prefill 1752 on the current binary). At **768k** DCA-on lands at **0.984**
(−1.2 pp vs 512k, comfortably inside the 0.96–1.0 band — no cliff at 3× the native cap; the fresh-binary
rerun (2026-07-13, `_dcaon_rerun`, n=50 `fresh_empty=0`, 9/50 hitting the short gen cap with the answer
present) lifted 768k **+2.8 pp** from the original-binary 0.956, with prefill **1408** / gen **55** tok/s
and wall **8h02m** — the last rung to move onto the current engine). At **1M** (the final rung, 4× the 256k
native cap, `n_ctx_train`=262144) DCA-on lands at
**0.916** (◇ — the current fixed-binary `_dcaon_rerun`, 2026-07-13; history 0.876 pre-fix / 0.716
server-crash artifact in the footnote). That is a **mild −6.8 pp** vs 768k (0.984), **not** a cliff:
variable-tracking softens gently at 4× native (0 empties, 20/50 hitting the short gen cap with the answer
present) rather than breaking. The soften is **not** generation-truncation (VT caps gen at 120 toks; the
20/50 "length" finish-reasons used the full short cap with the answer present, 30/50 "stop"). Current
binary: **prefill 1176 tok/s, gen 46.4 tok/s** on a 1.05M-token prompt, wall **12.6 h** (was ~24 h on the
original binary); peak VRAM ~70 GB (model 48.2 + KV 20.8 + compute 3.2 GB). **The whole ladder is now
re-confirmed on the shipping engine (#654):** DCA-on holds 256k (0.964) → 512k (0.996) → 768k (0.984) →
1M (0.916) — all four rungs now on the fresh binary — with only a gentle step down at 1M and **no
server-death artifact** (`fresh_empty=0` at every rung). The original-run history — first 1M attempt crashed after sample 40 on 2026-06-15, 9-sample re-fix
2026-07-01 giving 0.876 — is retained in the ◇ footnote.

### 1a-yarn. `--dca-yarn-factor` (bug-740 / patch 0087) — characterized NO-WIN

The `--dca-yarn-factor` flag was plumbed end-to-end but **never read** by the rope path (inert; bug-740).
Patch `0087` wires it into `build_dca_rope` as the YaRN **mscale**: `dca_attn_factor = attn_factor *
cparams.dca_yarn_factor` → `ggml_rope_multi`/`ggml_rope_ext`. Host-only; default 1.0 is byte-identical
(`×1.0f` bit-identity). Empirically characterized on **Qwen3-4B** (native 40960, DCA chunk 16384, RULER
5-needle substring under `ignore_eos` — never greedy-first-token):

| KV | ctx | ×native | yarn 1.0 | 1.1 | 1.25 | 1.5 | 2.0 |
|----|-----|---------|----------|-----|------|-----|-----|
| f16  | 98304  | 2.4× | **5/5** | — | 4/5 | 1/5 | 0/5 |
| q8_0 | 163840 | 4.0× | **5/5** | — | — | — | — |
| q8_0 | 204800 | 5.0× | 3/5 | — | — | — | — |
| q8_0 | 245760 | 6.0× | **4/5** | 4/5 | 4/5 | — | — |

**Verdict:** the mscale lever has **no beneficial regime** for DCA retrieval — at 6× native (where plain-DCA
is stressed) yarn 1.0/1.1/1.25 are flat at 4/5, and 1.18 is the *principled* mscale for 6× (`0.1·ln 6 + 1`),
so there's no missed sweet spot; pushing harder (1.5/2.0) only **over-sharpens** already-concentrated
attention and destroys retrieval. **Default 1.0 is correct.** Ships as a documented power-user knob, not a
win over plain-DCA. (Rejected the alternative full-YaRN `ext_factor` recipe — it would double-extend
positions vs DCA's chunk remap.)

**Cross-check — gemma 128e-Q6_K quick re-validation ladder (2026-06-25, current post-#554/#555 binary).**
n=15 RULER-VT (0–100), **f16/f16 KV** both, DCA chunk 8192, **Gemma-4-A4B 128e-Q6_K** weights (VERIFIED:
`load_model` loads `128e-Q6_K.gguf`, and the load log reports `n_ctx_train = 262144` ⇒ **native 256k** — the
ladder banner's "128e-F16" string is stale; early-prefill ~8.9k tok/s is Q6_K-class, ~12× the post-#555 F16
~3.1k). Confirms **plain-DCA alone holds the VT band deep into extension**. prefill tok/s = cumulative avg at
full ctx (early clips ~8.9k, degrades as the O(n) cache fills); wall approximate (two GPU lanes interleaved).

| ctx | ×native (256k) | DCA | VT (n=15) | prefill tok/s (avg@full) | gen tok/s | ≈wall |
|-----|----------------|-----|-----------|--------------------------|-----------|-------|
| 32768  | 0.125× | off | **100.0** | (fast) | 124.5 | ~1 min |
| 262144 | 1×     | off | **97.33** | — | 117.3 | ~16 min |
| 262144 | 1×     | on  | **98.67** | — | 118.0 | ~17 min |
| 524288 | 2×     | on  | **100.0** | 2,475 (211 s / 512k) | 80.0 | ~54 min |
| 786432 | 3×     | on  | **92.0**  | 1,859 (422 s / 786k) | 49.0 | ~108 min |

DCA-on ≥ off at the comparable 256k (1×) cell (98.67 ≥ 97.33), holds **100.0 at 512k (2×)**, lands **92.0 at
768k (3×)** — consistent with §1's careful n=50 768k = 0.984 (the −VT is n=15 sample noise, not a cliff). 1M
(4×) was not re-run today. **NB:** §1's "128k native cap / 8×" wording is an error — `n_ctx_train` is **256k**,
so 1M = 4× native (matches §1's own "3× at 768k").

### 1b. MRCR (OpenAI Multi-Round Co-reference Retrieval) — `sequence_matcher_ratio`

Perf columns are authoritative `summary.json` `scores` values. `n` = samples in the bin. `wall/req` =
median seconds per request (`wall_s_median`).

| ctx (bin) | DCA | score | n | prefill tok/s | gen tok/s | VRAM peak | wall/req (med) | status |
|-----------|-----|-------|---|---------------|-----------|-----------|----------------|--------|
| 256k | off | **0.1138** | 50 | 535.3 | 92.4 | 55,075 MiB | 336 s | **n=50 re-run (06-14)** |
| 256k | on  | **0.1320** | 50 | 555.5 | 89.5 | 55,075 MiB | 323 s | **n=50 re-run (06-14)** |
| 512k | on  | **0.1027** | 50 | 527.5 | 70.2 | 61,333 MiB | 833 s | **n=50 re-run (06-14)** |
| 768k_synth | on | **0.1259** | 8 | 477.5 | 50.7 | 69,063 MiB | 1971 s | done (small-n, not re-run) |
| 1M   | on  | **0.0273** | 6 | 489.1 | 55.2 | 73,111 MiB | 1653 s | done (small-n, not re-run) |
| 256k **(q8-KV)** | on | **0.0999** | ? | — | — | — | — | quant-KV × DCA (#434); C-series binary, `mrcr_256k_dcaon_q8_c1`, landed 06-24 |

*The **256k/512k cells were re-run at n=50** (driver `bs2:/srv/ml/omk_mrcr_dca/mrcr_n50_2gpu.sh`, cells
`mrcr_256k_dcaon mrcr_256k_dcaoff mrcr_512k_dcaon`; last cell — 512k — finished 06-14 15:21 CEST);
768k_synth/1M remain at their original n=8/6. `score`/`n`/`per_needle` are the authoritative n=50
`summary.json` `.score`; the throughput columns (prefill/gen tok/s, VRAM, wall/req) are per-ctx-bin
properties from the ladder `server.log`s and are independent of sample count. **The earlier small-n
numbers (256k-off 0.0437 / 256k-on 0.0497 / 512k-on 0.0483 at n=16/8) are superseded** — MRCR has
brutal per-prompt variance, so n=16 badly under-estimated the bin mean.*

**Reading (n=50).** At 256k (the only directly-comparable bin) DCA-on **0.1320 ≥** DCA-off **0.1138** —
DCA costs nothing and is marginally higher, and it leads at every needle count: on `per_needle_mean
= {2: 0.104, 4: 0.198, 8: 0.091}` vs off `{2: 0.099, 4: 0.154, 8: 0.086}`. This is the load-bearing
MRCR result and it strengthens at n=50 vs the old n=16 (where the +0.006 gap was within noise).
512k DCA-on is **0.1027** (`{2: 0.156, 4: 0.058, 8: 0.094}`) — lower than 256k-on, but a *different*
prompt bin, so this is **not** a "DCA degrades with ctx" signal (see the bin-comparability warning
above). The higher 768k_synth score (**0.1259**, still small-n=8) is NOT "DCA gets better at longer
ctx" — it's a synthetic bin whose per-needle mix is dominated by the easy **2-needle** sub-case
(`per_needle_mean = {2: 0.290, 4: 0.033, 8: 0.019}`). MRCR absolute scores are intrinsically low
(brutal fuzzy-retrieval bench); only same-bin comparisons (and the per_needle breakdown) are meaningful.

**Quant-KV × DCA @256k (composition, #434).** `q8_0` KV-cache + DCA-on at 256k scores **0.0999**
(`mrcr_256k_dcaon_q8_c1`, canonical `scores.metric = sequence_matcher_ratio`; `n` not emitted) — i.e.
**below even f16-KV DCA-*off* (0.1138)**. So on the hard MRCR task at 256k, **f16 KV fidelity matters more
than DCA does**: the q8 KV quality loss (≈ −0.032 vs f16 DCA-on 0.1320) outweighs the DCA gain (+0.018 vs
f16 off). Caveat — this is **cross-binary**: q8 ran on the C-series binary while the f16 ladder above is the
original bs2 ladder binary, and the same-binary f16 C-series cells (`mrcr_256k_dca{on,off}_c1`) produced no
scored `summary.json`, so the clean same-binary q8-vs-f16 delta is still missing. Consistent with §5b's rule
(*scalar KV → noDCA/f16-fidelity is the quality path*): for long-ctx retrieval, prefer f16/high-bit KV over a
DCA-on low-bit cache when quality is the priority. RULER-VT (easy retrieval) is far more quant-tolerant (§1a).

### 1c. Reference (superseded) — v7-coder-it 98e Q4_K_M, MRCR DCA-on (bs2)

These upper-tier MRCR cells were run earlier on a **different model** (98e v7-coder Q4_K_M, not
128e-F16), so they are not part of the single-model ladder; the 128e-F16 re-runs above replace them.
**Same-bin head-to-head** (768k_synth): 128e-F16 **0.1259** beats v7-coder **0.0376** by 3.3×, as
expected for a clean F16 base vs a 98e-pruned Q4_K_M. Authoritative `scores` perf:

| ctx (bin) | score | n | prefill tok/s | gen tok/s | VRAM peak | wall/req (med) | per_needle_mean |
|-----------|-------|---|---------------|-----------|-----------|----------------|-----------------|
| 512k | 0.0413 | 8 | 3081.9 | 57.0 | 26,827 MiB | 208 s | {2: 0.053, 4: 0.024, 8: 0.049} |
| 768k_synth | 0.0376 | 8 | 1815.9 | 33.9 | 35,227 MiB | 739 s | {2: 0.049, 4: 0.044, 8: 0.011} |
| 1M | 0.0033 | 6 | 2052.9 | 38.2 | 39,629 MiB | 606 s | {2: 0.0023, 4: 0.0, 8: 0.0076} |

(v7-coder Q4_K_M is ~3.5× smaller on disk, so its prefill tps run far higher and VRAM far lower than
the F16 ladder model — these rows are NOT throughput-comparable with §1b.)

---

## 2. Throughput — prefill / gen tps (32k ctx, 4-chunk)

### 2a. 3-arm gen-tps — gemma-4-26B-A4B-it **Q4_K_M**, solidpc RTX 3090 (#620)

22,722-token prompt, 256 gen tokens, ctx 32768, chunk 8192.

| arm | prefill tok/s | gen tok/s | gen ratio |
|-----|---------------|-----------|-----------|
| vanilla (stock llamafile) | — | — | stock binary segfaulted at load (N/A) |
| DCA build, `--dca off` | 2587.0 | 71.31 | 1.000 (baseline) |
| DCA build, `--dca on` | 2558.6 | 65.96 | **0.925** |

→ Turning DCA **on** costs ~7.5% gen throughput at 32k (the runtime-flag cost); prefill is at parity (2559 vs 2587).
The DCA build with `--dca off` is the right non-DCA baseline (the stock vanilla binary can't load this model build).

### 2b. Per-arch coherence-gate timings — solidpc RTX 3090 (32k ctx, 200 gen tokens)

DCA-on (fused) unless noted. Confirms the head-dim port works across arches:

| model | arch | head_dim | prefill tok/s | gen tok/s |
|-------|------|----------|---------------|-----------|
| Qwen3.6-35B-A3B UD-IQ3_XXS | qwen35moe | 256 | 1787.2 | 60.61 |
| Qwen3-4B Q4_K_M | qwen3 | 128 | 4355.9 | 75.45 |
| v7-coder-it 98e Q4_K_M — **native** (DCA off) | gemma4 | 512 | 2779.6 | 70.16 |
| v7-coder-it 98e Q4_K_M — **fused** (DCA on) | gemma4 | 512 | 2773.2 | 66.01 |

→ On the same gemma model, DCA-on vs off at 32k: prefill 2773 vs 2780 (parity), gen 66.0 vs 70.2 (~0.94×) — consistent with §2a.

### 2c. Optimization history (prefill at 256k, documented in 0078-dca.patch)

After **O9** (analytical INTRA mask — kernel-derived causal band) the multi-chunk DCA prefill at
256k is **at parity with native (~1.0×)**, down from the pre-optimization **1.59×** penalty. O6
(analytical SUCC/INTER band bounds) killed 2 of 3 dense masks; O3 gave the multi-chunk 3× KV floor.

---

## 3. Memory model — iSWA KV scaling (128e-F16, bs2 Blackwell)

The reason a 262144-trained 26B-A4B fits 1M context on one GPU: **only the 5 global-attention
layers scale KV with full context**; the 25 SWA layers are pinned to a 1536-cell sliding window.

| Component | 256k | 512k | 768k | 1M (proj) |
|-----------|------|------|------|-----------|
| Weights (F16, fixed) | 48,150 MiB | 48,150 | 48,150 | 48,150 |
| KV — 5 global layers (scales) | 5,120 MiB | 10,560 | ~17,280 | ~20,800 |
| KV — 25 SWA layers (fixed 1536-win) | 300 MiB | 300 | 300 | 300 |
| Compute buffer | ~820 MiB | ~1,636 | ~2,500 | ~3,000 |
| **Total (observed / projected)** | **~54.5 GB** | **61.3 GB** (obs) | **69.1 GB** (obs) | **~72 GB** (proj) |

All tiers fit the 96 GB Blackwell with headroom (1M ≈ 72 GB < 96 GB). On a 24 GB 3090, only
≤256k of the **quantized** model fits; F16 at any long ctx is bs2-only.

---

## 4. Correctness gates

### 4a. Qwen multi-chunk coherence — `dca_gate623_mc_coherence.sh` (solidpc, DSO `df4c46bc`, #623)

Multi-chunk (ctx 32768 > chunk 8192 → 4 chunks). Bar: fused (DCA on) coherent and ideally
byte-identical to native (DCA off = full-attention ground truth).

| model | head_dim | native vs fused | verdict |
|-------|----------|-----------------|---------|
| Qwen3.6-35B-A3B (qwen35moe) | 256 | **byte-identical** (470 ch, uniq 0.38, 7/7 record-lines) | **PASS** |
| Qwen3-4B (qwen3) | 128 | **byte-identical** (463 ch, uniq 0.366, 7/7 record-lines) | **PASS** |
| OmniMerge v4 (qwen35, MTP) | 256 | **near-identical** (native 557 ch / fused 556 ch, uniq 0.713≈0.714, max_run 1, 9/9 record-lines) | **PASS** |

OmniMerge v4 is a Qwen3-Next **hybrid** (65 blocks: ~48 SSM/GatedDeltaNet linear-attn + 16 full-attn
hd256 + 1 MTP/nextn head at `blk.64`). It would not load until the **#622** loader fix: (a) qwen35
hparams now reads `nextn_predict_layers` and excludes the MTP block from the recurrent/transformer
loops, (b) the tensor-load path loads `blk.64.nextn.*` (not ssm/attn) for the last `nextn_predict_layers`
blocks, (c) `llm_build_qwen35` skips the MTP block in forward, and (d) `llama-arch.cpp` re-classified the
six `NEXTN_*` tensors `LLM_TENSOR_LAYER_OUTPUT → LLM_TENSOR_LAYER_REPEATING` (matching upstream — they
are stored per-block, so the loader must not fault on the block index). DCA only chunks the 16 hd256
full-attn layers on this hybrid, so its marginal long-context value here is narrower than on a
pure-attention model — but the fused multi-chunk path is verified coherent. See `.wolf/buglog.json`
bug-458.

The prior DSO (build #3, `65b324b1`) emitted solid `!` (NaN logits) on both — the iter `Q_in_reg`
fix was the load-bearing final site. See `.wolf/buglog.json` bug-454/455/456 and `.wolf/cerebrum.md`.

### 4b. Gemma no-regression — `dca_gate_gemma_mc_regress.sh` (solidpc, DSO `df4c46bc`)

The qwen fix is **provably a no-op on Gemma**: the ampere config table (`ggml_cuda_fattn_mma_get_config_ampere`)
has `nstages_target=1, Q_in_reg=false` for every DKQ=512 row, so all four fixes compile to the
identical Gemma kernel and dispatch `case 512` == the old hardcoded `<512,512>`. Empirical confirmation
(v7-coder Q4_K_M, hd512):

| mode | native vs fused | note |
|------|-----------------|------|
| single-chunk (n_ctx ≤ chunk) | **byte_identical = True** | both arms route to plain FA; binary is deterministic, DCA single-chunk is bit-exact |
| multi-chunk (n_ctx > chunk) | native ≠ fused (uniq 0.297, coherent, 7 records, no loop) | intrinsic Q4_K_M band-combine numerics tipping greedy argmax — **pre-existing, not the qwen fix** |

The authoritative Gemma DCA-quality measure is the bs2 128e-F16 ladder (§1), where fresh-binary 256k
dcaon 0.964 = dcaoff 0.964 (exact parity, both n=50) confirms multi-chunk DCA preserves quality on the
real model/metric.

### 4c. NIAH single-needle retrieval — `dca_niah_ladder_618.sh` (bs2, 128e-F16, #618)

Needle (code `73914`) retrieved from the greedy completion, DCA-on, single prefill per cell
(native==fused established byte-exact). Chunk-count ladder:

| chunks | ctx | result |
|--------|-----|--------|
| 2 | 16k | PASS (retrieved) |
| 4 | 32k | PASS |
| 8 | 64k | PASS |
| 16 | 128k | PASS |
| 32 | 256k | PASS |

(Per the #618 ladder + the 0078-dca.patch measured-perf note; raw responses at
`bs2:/srv/ml/dca/dca_niah_ladder_618/resp_c*.json`.)

### 4d. Decode chunk-boundary correctness (#635) — `dca635_fix_gate.sh` + NIAH INTER-band (solidpc, Qwen3-8B-Q8_0)

The #635 decode fix (`INTER-Q = 2c`; full RCA in `docs/DCA_HANDOFF.md` §6) is gated two ways, greedy
(temp=0, top_k=1, seed=1, `cache_prompt=false`).

**(i) Self-calibrating count-up.** DCA-on must break NO EARLIER than the model's *intrinsic* limit.
Qwen3-8B-Q8_0 degenerates by itself (an intrinsic weakness, NOT a DCA bug), so "never breaks" is the
**wrong** criterion — the gate measures the DCA-off intrinsic on the *same* binary, then PASSes DCA-on
iff each chunk reaches it. (`n_predict=1600`; the old 900 truncated at ~206 and manufactured a fake
break@206.) The intrinsic value is decode-path-dependent (~326 on the earlier single-block-per-tile
hack, **346** on the clean stream-k binary) — exactly why the gate self-calibrates rather than
hard-coding a number.

**CONFIRMED on the clean deployable binary** (host sha `7c696dde`, stream-k decode + 2c fix; kernel
hack + host probes reverted), 2026-06-14:

| arm | chunk | count reached | verdict |
|-----|-------|---------------|---------|
| off (intrinsic) | — | **346** | reference |
| on | 256 | **346** | PASS |
| on | 512 | **346** | PASS |
| on | 1024 | **346** | PASS |

Pre-fix, DCA-on collapsed ~2× early (c256 ≈ 151, c512 ≈ 299) into `…232323…` garbage.

**(ii) NIAH through the INTER band.** Needle (code `73914`) in chunk-0 + ~3000 filler tokens, so the
retrieval query is at `cq ≥ 2` and the needle sits in the **INTER band** — exactly where the 2c fix
relocates far keys (rel `[c,2c]`). On the clean binary, DCA-on(2c) c256 retrieves `73914` **as well as
DCA-off** (both FOUND) → the fix preserves far-context retrieval (the one production risk of pushing far
keys past the window edge). Probe-free runner: `dca635_niah_clean.sh`.

Scripts: `solidpc:backup_models/scripts/dca_chunkprobe/{dca635_fix_gate.sh,dca635_niah_clean.sh,dca635_niah/}`.
The decisive diagnostic — an independent absolute-position full-attention reference — is `dca635_true_ref.py`.

> **Status: CONFIRMED (2026-06-14 21:27 CEST).** Both gates above pass on the clean deployable artifact —
> `ggml-cuda.so` rebuilt with the falsified single-block-per-tile decode hack reverted (stream-k
> restored), host binary relinked with the capture probes stripped (sha `9f51da03` → `7c696dde`), 2c fix
> preserved. `0078-dca.patch` regenerated from this tree (37 files, 224K): 2c fix present, zero
> `dca635` / `DCA635_FORCE_STREAMK` / `dca635_dump` / `dca635_capture_cb` tokens.
>
> ✅ **#617B debug instrumentation STRIPPED (2026-06-14).** The four inert artifacts that previously rode
> along on the fragmented (context-shift) path — a `DCA617B_FORCE_FRAG` env backdoor, two one-shot
> `[DCA617B] BUILD/FILL` stderr prints, and the `DCA617_SUCC_NULL/INTER_NULL` env blocks — were removed
> from `dca.cpp` (`build_attn_inp_dca`) and `llama-kv-cache.cpp` (`set_input_dca`). All were nullptr/no-op
> on the fast path and only reachable via explicit env vars, so removal changes **no** production behavior.
> Host `make` rebuilt the binary (sha `665bd58b`, was `7c696dde`); the **#634 ctx-shift gate was re-run on
> the stripped binary and still PASSES** (off + on2048 both PASS-coherent, 1 shift, monotone 1201→2400,
> byte-identical — §4e below). `0078-dca.patch` regenerated: **37 files, 220K, zero `DCA617*` tokens**, the
> #635 2c fix (`pqn[off] = 2*c`) intact, the #617B `is_fragmented`/`mask_succ` machinery intact. The
> `FORCE_FRAG` test hook (dense path on a contiguous cache, no n_ctx overflow needed) is preserved as a
> documented one-line re-add in `DCA_HANDOFF.md §10` optional tasks, not in production source.

### 4e. Context-shift coherence (#617B / #634) — `dca_ctxshift_qwen3.sh` (solidpc, Qwen3-4B-Q4_K_M)

#617B restores correctness after a **classic context shift** (generation overflows `n_ctx` → `seq_rm`
+ `seq_add` relabels `pos[]` in place, so cache index ≠ position and the analytical INDEX bands select
the wrong cells — the model collapses to a token-loop). The fix is a sticky `is_fragmented` latch gating
a dense **position-based** SUCC/INTER/INTRA fill. Reachable **only on full-attention DCA archs
(qwen2/3/3.5)** past n_ctx — gemma4 (the 1M iSWA target) disables KV-shift entirely, so it never fragments.

That fragmented fill lives in the same `set_input_dca` as the #635 `INTER-Q = 2c` change (the 2c fill is
unconditional, so it now governs the fragmented path too), so the gate was **re-run against the clean 2c
binary** (host sha `7c696dde`), 2026-06-14. A real shift is forced: ctx=8192, chunk=2048 (4 DCA chunks),
~4.9k-token counting prompt + `ignore_eos` gen=6000 → n_past overflows 8192 → ≥1 classic shift.

| arm | dca | shifts | gen ints | first (exp 1201) | longest run | maxrep | verdict |
|-----|-----|--------|----------|------------------|-------------|--------|---------|
| off | native (ref) | **1** | 1200 | 1201 | 1200 | 1 | **PASS-coherent** |
| on2048 | DCA modular shift | **1** | 1200 | 1201 | 1200 | 1 | **PASS-coherent** |

Both count perfectly monotone **1201→2400** across the shift (`longest_run == gen_ints`, no repeats), and
DCA-modular matches native byte-for-byte. The 2c fix does not regress the context-shift path — **#634 closed.**

---

## 5. KV-quantization × DCA — full-vocab PPL + KL-divergence (#446, solidpc RTX 3090)

`real_frac` (logit-equivalence) is **argmax-only** — it cannot distinguish genuine distribution-
faithfulness from argmax-coincident degradation. This section adds the whole-distribution instrument:
**teacher-forced full-vocab KL-divergence** over a fixed corpus. Per regime ({DCA-off, DCA-on}) we write
an **f16 logits reference** (`--kl-divergence-base`), then score every KV-quant candidate against it
(`--kl-divergence`). The corpus is teacher-forced, so every config decodes the *identical* token
sequence and `KL(candidate ‖ f16)` is exactly aligned per token. This is the decisive answer to #446.

**Methodology.** Model **Qwen3-8B-Q8_0** (head_dim 128 → `innerq-scale-128`), corpus wikitext-2 test
slice (6402 tokens), `-c 2048`, 3 chunks, `--flash-attn on -ngl 99`, teacher-forced. DCA recipe
`--dca on --dca-chunk-size 1024`. Runner `.opencoti/ppl-kld-matrix.sh` on a **GPU-enabled standalone
perplexity binary** (`.opencoti/ppl-link.mk` + `ppl_main_gpu.cpp`, a `main()` wrapper that calls
`llamafile_has_gpu()` so the CUDA DSO loads and `-ngl` offloads — the stock `tools/perplexity/main.cpp`
never triggers that load, so vanilla perplexity is CPU-only). DCA was exposed to perplexity via a
**temporary** `arg.cpp` edit adding `LLAMA_EXAMPLE_PERPLEXITY` to `--dca`/`--dca-chunk-size`
(reverted after the eval; vendor tree restored to patch-stack state — the edit is *not* in any patch).
`KLD` = mean nats; `top%` = same-top-token agreement vs the f16 reference.

### 5a. TurboQuant symmetric — the #446 decider

f16 reference (Final-estimate PPL): **noDCA 9.451 · DCA(chunk 1024) 9.441**.

| tier (`-ctk`=`-ctv`) | PPL(Q) noDCA | KLD noDCA | top% noDCA | PPL(Q) DCA | **KLD DCA** | top% DCA |
|----------------------|--------------|-----------|------------|------------|-------------|----------|
| turbo8 (8-bit) | 9.438 | 0.00173 | 98.2 | 9.463 | **0.00217** | 98.1 |
| turbo4 (4-bit) | 10.39 | 0.142 | 85.1 | 9.913 | **0.115** | 86.3 |
| turbo3 (3-bit) | 12.71 | 0.404 | 75.5 | 10.11 | **0.186** | 82.7 |
| turbo2 (2-bit) | **1584** | **5.596** | **16.1** | 14.71 | **0.647** | 67.5 |

**Verdict — `real_frac=0` for turbo-DCA is GENUINE, not argmax-coincident.** Under DCA the KLD is
**monotone in tier bits** (turbo8 ≈ 0.002 near-lossless → turbo2 0.65 lossy-but-functional) — the
signature of a *faithful* `dca_lift_to_f16` dequant (#444 → #385 turbo→f16 CPY kernel). The
whole-distribution metric corroborates the #446 argmax gate: the turbo-DCA distribution genuinely
tracks f16-DCA; where the argmax flips, the flips are near-ties, not degradation.

**Bonus — the DCA f16-lift is the *better* turbo path.** For turbo2/3/4 the DCA KLD is **lower** than
the noDCA in-register FA-VEC read (turbo8 a tie). The extreme case is decisive: **turbo2 in the noDCA
in-register path is degenerate** — KLD 5.60, PPL ×168 (1584), top 16% (~random) — while **turbo2-DCA
via the faithful lift is healthy** (KLD 0.647, top 67.5%). The argmax-tolerant L4 gate (#394) masked
this; full-vocab KLD exposes it. **Recommendation: turbo2 only via the dequant-on-lift path (DCA, or
the #444 quantized-DCA f16 slot) — never the in-register noDCA read.** (`.wolf/buglog.json`
turbo2-inreg.)

### 5a-TCQ. Trellis-coded tiers (#447) — noDCA in-register, current DSO

TCQ (`turbo3_tcq`/`turbo2_tcq`) is **always-fuse** (no f16 dequant-on-lift yet), so the in-register
symmetric read IS the path under test. Same #446 instrument (Qwen3-8B-Q8, wiki, ctx2048/chunk1024),
**current DSO**, `TURBO_TCQ_ALPHA_V=1.0`. The turbo8/4/3/2 controls re-ran here **bit-identical** to
§5a → the TCQ Stage-1–4 shared-file edits did not move the non-TCQ tiers (second instrument
confirming "not a regression", beyond the real_frac controls).

| tier (bpv) | PPL(Q) | KLD | sametop% | vs scalar sibling |
|---|---|---|---|---|
| turbo3_tcq (3.25) | 10.306 | **0.200** | 83.0 | **2× better than turbo3** (0.404); turbo4-class |
| turbo2_tcq (2.25) | 1113 | **5.215** | 18.6 | ≈ turbo2 (5.60) — degenerate in-register |

**turbo3_tcq is a genuine win.** 0.25 extra bits over scalar turbo3 buys a **2× KLD reduction**
(0.404→0.200), landing between turbo4 (0.142) and turbo3 — the trellis delivers, corroborating the
real_frac=0 needle gate with the whole-distribution instrument. **turbo2_tcq is NOT viable
in-register** (KLD 5.2, sametop ≈ random): the 2-bit-class collapse is below the in-register floor
even on Qwen3-8B, exactly like scalar turbo2. The floor is sharper on small already-Q4 models — on
Qwen2.5-1.5B-Q4 even turbo3_tcq collapses (real_frac 1.0), tracking turbo3 (also 1.0 there). Whether
this in-register low-bit collapse is a **kernel defect** or **model fragility** is settled decisively by
the target-class run below: it is **fragility**. The f16 inverse-FWHT/trellis dequant-on-lift (mirrors
#385/#444) remains a worthwhile *optional* enhancement for small-model support, but it is **not** a
prerequisite for shipping TCQ on the actual targets.

### 5a-TCQ-27B. Target-class verdict (#447/#504) — Qwen3.6-27B, the model-vs-defect decider

The §5a/§5a-TCQ numbers above are an **8B** instrument; the question they leave open — *is the
in-register low-bit collapse our kernel or the model?* — can only be answered on the model class the
[anbeeld.com KV-quant benchmark](https://anbeeld.com/articles/kv-cache-quantization-benchmarks-for-long-context)
actually used: **Qwen 3.6-27B**. Same harness (`.opencoti/tcq-ppl-27b.sh`), 320 KB wikitext, ctx 2048,
**InnerQ OFF** (proven inert), `TURBO_TCQ_ALPHA_V=1.0`, f16 KLD-base. Model:
`Qwen3.6-27B-Omnimerge-v4-Q4_K_M` (f16 base PPL 6.307).

| tier (bpv) | PPL(Q) | KLD | sametop% | 8B KLD (320 KB) | anbeeld ref KLD | ours ÷ ref |
|---|---|---|---|---|---|---|
| turbo8 (8) | 6.317 | **0.0168** | 97.7 | 0.0025 | q8 0.0023 | 7.3× |
| q4_0 (4, scalar anchor) | 6.334 | 0.0250 | 96.8 | 0.028 | 0.0047 | 5.3× |
| turbo4 (4) | 6.349 | 0.0342 | 95.7 | — | 0.0048 | 7.1× |
| turbo3_tcq (3.25) | 6.389 | **0.0366** | 95.6 | 0.187 | 0.0080 | 4.6× |
| turbo3 (3) | 6.407 | 0.0470 | 94.7 | 0.350 | 0.0112 | 4.2× |
| turbo2_tcq (2.25) | 6.456 | **0.0709** | 92.7 | ~5.19 | 0.0231 | 3.1× |
| turbo2 (2) | 6.697 | 0.0960 | 90.8 | ~6.4 | 0.0362 | **2.65×** |

**Verdict — it is the model, not the implementation.** turbo2 went from **PPL ~3000 / KLD 6.4
(collapse) on the 8B** to **PPL 6.70 / KLD 0.096 (functional) on the 27B** — same code, same harness,
only the model changed. The entire ladder is monotone and functional (every cell within 0.4 PPL of the
6.307 base), and **both TCQ tiers beat their plain-turbo siblings** (turbo3_tcq 0.0366 < turbo3 0.047;
turbo2_tcq 0.0709 < turbo2 0.096) — turbo2_tcq's 2.25 bpv lands exactly between 3-bit and 2-bit, as
designed. This reproduces the reference's qualitative behavior on the reference's own model class.

**On the anbeeld gap.** Our absolute KLDs run ~3–7× the reference because the eval *setup* differs
(ctx 2048 vs 64k, 320 KB vs full wikitext, f16 base vs bf16) — and this tax is **model-independent**:
the same-code `q4_0` anchor is 0.025 on the 27B and 0.028 on the 8B, both ~5× the reference's 0.0047.
Crucially, **turbo2's ratio-to-reference (2.65×) is the *lowest* in the ladder** — far from anomalous,
the most aggressive tier is the best-behaved relative to the reference. There is no defect signal at
any bit-width.

**The fragility gradient (why the 8B looked broken).** In-register symmetric KV tolerance scales with
model KV-redundancy: **Qwen2.5-1.5B-Q4** collapses at ≤4-bit (turbo4/3/2/tcq all real_frac 1.0; turbo8
fine); **Qwen3-8B-Q8** is fine at 3-bit-degraded but collapses at 2-bit (PPL 3000); **Qwen3.6-27B**
absorbs even 2-bit cleanly. The in-register `vec_dot` approximation's loss (cf bug-583: turbo2
in-register KLD 5.60 vs faithful f16-lift 0.647 on *identical* data) is progressively absorbed by
larger models. **Conclusion for #504: the symmetric in-register noDCA path ships as-is on
27B-class / Gemma-4 targets** — turbo2/turbo2_tcq included. The f16 dequant-on-lift is reclassified
from "shippability blocker" to "optional small-model support." RULER quality-in-use on Gemma-4-A4B
tracked separately.

**DCA-on companion (same 27B, `--dca on --dca-chunk-size 1024`, per-regime f16+DCA base 6.304).** Under
DCA the turbo K/V route through the FAITHFUL f16 dequant-on-lift (#444/#446), not the in-register read —
isolating the lift path's quality at target scale. DCA is inert at ctx-2048 here (f16+DCA base 6.304 ≈
noDCA 6.307), so the cells are directly comparable to the noDCA ladder above:

| tier | KLD noDCA (in-reg) | KLD DCA (f16-lift) | Δ |
|---|---|---|---|
| q4_0 | 0.0250 | 0.0285 | +0.0035 (lift round-trip costs a hair on faithfully-read scalar KV) |
| turbo8 | 0.0168 | 0.0175 | +0.0007 (wash) |
| turbo4 | 0.0342 | 0.0316 | **−0.0026** |
| turbo3 | 0.0470 | 0.0436 | **−0.0034** |
| turbo2 | 0.0960 | 0.0896 | **−0.0064** |
| turbo3_tcq | 0.0366 | **composes (#533)** ⁵ | f16-lift now exists → DCA composes (was rc=134 in this 2026-06-21 run) |
| turbo2_tcq | 0.0709 | **composes (#533)** ⁵ | same |

⁵ **TCQ+DCA composition was RESOLVED by #533, verified 2026-06-30 (#505).** The `turbo{3,2}_tcq→f16`
dequant-on-lift kernels (`turbo-cpy.cu`, `opencoti-hook #533`) + `cpy.cu` dispatch + CPY `supports_op`
acceptance (`ggml-cuda.cu:5442`) were added when #533 fixed the TCQ prefill via an MMA-materialize, and
`dca.cpp`'s `dca_lift_to_f16` routes TCQ through them. Boot-compose check (solidpc 3090,
`Qwen3.6-27B-Omnimerge-v4-Q4_K_M`, `-ctk/-ctv turbo3_tcq --dca on --dca-chunk-size 1024`): **boots clean,
no rc=134, decodes coherently.** The KLD *value* under DCA was not re-measured (needs the `perplexity --dca`
arg.cpp edit; optional now that compose is proven) — cells show the noDCA KLD as the fidelity proxy.

**Reading.** (1) For turbo low-bit, the **f16-lift ≥ the in-register read at every bit-width, and the
margin widens as bits drop** (turbo4→turbo2: −0.003 → −0.006) — confirming the in-register `vec_dot`
approximation is the (small, on 27B) lossy element, exactly bug-583's thesis. The margin is small here
only because the 27B already absorbs the in-register loss; on the 8B the same lift rescued turbo2
6.4 → 0.647. (2) For scalars, noDCA is the quality path (DCA adds a lift round-trip) — the inverse of
turbo, matching §5b. (3) **TCQ+DCA composes as of #533** (was rc=134 SIGABRT in this 2026-06-21 run): TCQ
was then always-fuse with no `turbo_tcq→f16` kernel; #533 added exactly that kernel (for the prefill
MMA-materialize), which also gives DCA's `dca_lift_to_f16` a path to lift TCQ K/V — so the same #533 work
delivered both the prefill fix and TCQ+DCA composition. The remaining #505 item (small-model ≤8B *decode*
through the lift) is optional/off-target per #504. (Harness `.opencoti/tcq-ppl-27b-dca.sh`;
matrix `27b-dca-matrix.tsv`. Ran via a temporary `arg.cpp` LLAMA_EXAMPLE_PERPLEXITY edit, since reverted.)

### 5a-TCQ-CB. Codebook retrain & KLD-aligned objective campaign (#523–525, solidpc RTX 3090)

Goal: **lock the trellis codebook** before the deferred full PPL/KLD + tps + RULER campaign. Three
ordered steps on the §5a-TCQ-27B instrument (same binary/base/corpus: `perplexity` host build,
`Qwen3.6-27B-Omnimerge-v4-Q4_K_M`, 320 KB wikitext, ctx 2048, InnerQ OFF, `TURBO_TCQ_ALPHA_V=1.0`,
f16 KLD-base `base_f16_27b.dat`). Codebooks load **rebuild-free** via the A′ runtime path
(`TURBO_TCQ_CB` 512-entry / `TURBO_TCQ_W_CB` 1024-entry). Lower KLD = better.

**Bars to beat** (deployed = shipped buun codebook): turbo3_tcq deployed-512 **0.036648** ·
v1-synthetic-1024 0.036972 · v1-synthetic-512 0.038815. Free-widen win condition: `turbo3_tcq_w`
(1024-state, real-27B-trained) KLD **< 0.036648** at identical 3.25 bpv.

**Gate log** (`.opencoti/tcq-gate1.sh` → `.opencoti/ppl-kld/27b_fe_*.log`, `27b-fe.tsv`):

| date | gate | cell | codebook | bpv | KLD | sametop% | verdict |
|---|---|---|---|---|---|---|---|
| 06-21 | 1 | tcq_ctrl_v2 | deployed-512 (anchor) | 3.25 | **0.036648** | 95.64 | ✓ reproduces bar exactly — GPU/harness/binary sound |
| 06-21 | 1 | tcq_real512_v2 | real27b-512 (MSE) | 3.25 | 0.037559 | 95.40 | **> deployed** — fresh MSE retrain is *worse*; MSE exhausted (tail-share deficit) |
| 06-21 | 1 | tcq_real1024_v2 | real27b-1024 (MSE widen) | 3.25 | 0.037269 | 95.75 | **> deployed**, < real512 — MSE+free-widen still short of 0.036648; Step-2 needed |
| 06-21 | 1 | scalar_q5_0_rt | q5_0 (frontier) | 5.5 | _interrupted_ | — | cut at chunk 15 (~0.036 running) by session /exit 12:41 — NOT a fault; rerun as scalar_q5_0_rt2 in gate-2 |

**Reading so far.** The anchor's exact reproduction (0.036648) certifies the post-reboot binary/DSO.
The MSE-512 retrain at **0.037559 > 0.036648** is the decisive negative: a from-scratch MSE codebook
on the real-27B dump **cannot beat** the deployed one, because the deployed codebook carries more
*tail* point-share than MSE optimization yields (post-FWHT marginals are ≈N(0,1), so diagonal/Fisher
weighting is near-dead and MSE over-resolves the centre). KLD rewards tail resolution → MSE is the
wrong objective. **The MSE-1024 free-widen confirms it: 0.037269** — better than MSE-512 (0.037559, so
doubling trellis states 512→1024 *does* help) but still **> deployed 0.036648**, and even > v1-synthetic-1024
(0.036972). **Step 1 is settled negative:** no MSE codebook (512 or widened-1024) beats the shipped
tail-heavy one — the win must come from the *objective*, not the state count. Empirical green-light for
**Step 2** (KLD-aligned tail-weighted distortion `w(v)=1+λv²`, λ-sweep; gate-2 picks the λ whose 1024
codebook beats 0.036648).

**Events.** *2026-06-21 11:30* — the **first** gate-1 attempt aborted mid-run when the **RTX 3090
fell off the PCIe bus** (NVRM **Xid 79** → **Xid 154 "Node Reboot Required"**); every cell, incl. the
deployed anchor, hit `unspecified launch failure` — a **hardware fault, not a TCQ/codebook
regression** (DSO byte-identical, codebooks correctly sized, anchor used no override; **bug-621**).
Host rebooted, GPU recovered clean (xid=0), gate-1 re-running from 12:04 (numbers above are the clean
run). *Step 2* λ-sweep (`w(v)=1+λv²`, λ∈{0,0.5,1,2,4}, CPU, `.opencoti/tcq-step2-lambda-sweep.py`)
running in parallel. *Step 3* (asymmetric `turbo3_tcq_w`-K / `turbo2_tcq`-V wide-K/cheap-V, ~2.75 bpv)
pending a ~72-min CUDA rebuild (`.opencoti/step3-activation-edits.md`).

**Step-2 pivot — warm-start from the deployed codebook (#524).** Since Step-1 proved a *cold* MSE/widen
retrain can't reach 0.036648, the cold λ-sweep was retired for the direct form: **seed the GLA trainer from
the deployed-512 codebook, then refine on real-27B with a tail-weight λ that *holds* the deployed
tail-heaviness** (a λ=0 refine would erode it — the MSE M-step pulls levels back to the centre). 512 seeds
from deployed directly; the 1024 widen seeds via coset-aware group-halving (`1024 state (g<<3)|pos ←
deployed[((g>>1)<<3)|pos]`, duplicating each deployed level into the correct L=10 trellis pair). `restarts=1`
(stay in the deployed basin). Seed sanity: the loaded deployed seed measures tail>2.0=**9.8%** / >2.5=**3.7%**,
matching the shipped codebook exactly → domain/coset map verified. Trainer gained an `init_cb=` warm-start
hook; driver `.opencoti/tcq-warmstart.py`. This strictly dominates the cold sweep for "beat deployed" — it
*starts at* 0.036648 and can only hold or improve.

**Step-2 v2 — λ=1 overshoots; small-λ search (#524).** The first warm codebook trained, **ws1024 λ=1.0**,
converged cleanly (held-in weighted-distortion fell monotonically 0.144→0.051 over 20 iters — *not* a
numerical divergence) to a codebook with **tail>2.0=89.2% / >2.5=87.0%** — ~9× the deployed's 9.8%/3.7%.
So the weighted-MSE objective's *true optimum* at λ=1 is a tail-degenerate codebook that under-resolves the
centre where the KV bulk lives → it should hurt KLD badly (the high-λ calibration point). The lesson: the
λ→tail-share curve is brutally steep (λ=0 MSE → ~8.5%, λ=1 → 89%), so the deployed's mild ~10% tail sits at
*small* λ. The grid was corrected to **λ∈{0.05, 0.1, 0.2}** (1024-prioritised, the prize) + one λ=0
(MSE-refine) endpoint + one 512 check; the λ=2 cells were dropped (would over-shoot worse). ws1024_w1 (λ=1)
is kept and measured as the high-λ endpoint. (Side-effects of the redirect: scalar_q5_0_rt2 was cut mid-run
when gate-2 v1 was stopped, re-queued as rt3 — LAST.)

**Gate-2 log** (`.opencoti/tcq-gate2.sh`, file-gated on each warm codebook as it's trained):

| date | cell | seed | λ | bpv | tail>2.0 | KLD | sametop% | verdict |
|---|---|---|---|---|---|---|---|---|
| 06-21 | ws1024_w1 | deployed→1024 | 1.0 | 3.25 | 89.2% | 0.037051 | 95.64 | > deployed — λ=1 over-corrects |
| 06-21 | ws1024_w005 | deployed→1024 | 0.05 | 3.25 | 88.0% | **0.034034** | 95.71 | **< deployed (−7.1%)** ✓ |
| 06-21 | ws1024_w01 | deployed→1024 | 0.1 | 3.25 | 88.5% | **0.036303** | 95.55 | < deployed (−0.9%, marginal) ✓ |
| 06-21 | ws512_w01 | deployed-512 | 0.1 | 3.25 | 88.1% | 0.037681 | 95.50 | > deployed — 512 can't beat even warm; widen needed |
| 06-21 | ws1024_w02 | deployed→1024 | 0.2 | 3.25 | 89.0% | 0.037259 | 95.75 | > deployed — λ=0.2 over-corrects |
| 06-21 | **ws1024_w0** | deployed→1024 | **0.0** | 3.25 | 87.8% | **0.033130** | 95.70 | **★ WINNER — < deployed (−9.6%); plain MSE-refine** |
| 06-21 | scalar_q5_0_rt3 | — (q5_0) | — | 5.5 | — | _running_ | — | frontier rerun, LAST (tangential) |

(λ=2 cells dropped — superseded by the small-λ finding above; the warm-start grid was re-run accordingly.)

**Verdict — free-widen WINS; tail-weight REJECTED (#524 closed).** The decisive result inverts the Step-2
hypothesis. **`ws1024_w0` — the 1024-state free-widen, warm-started from deployed-512 and MSE-refined (λ=0) on
real-27B — is the new best: KLD 0.033130 vs deployed 0.036648, a 9.6% improvement at identical 3.25 bpv.** This
is the plan's free-widen win condition (`turbo3_tcq_w` 1024-state, real-27B-trained, KLD < 0.036648), achieved.
KLD is **monotone in λ from 0**: λ0 (0.033130) < λ0.05 (0.034034) < λ0.1 (0.036303) < deployed < λ0.2 (0.037259)
< λ1 (0.037051) — so **every tail-weight λ>0 regresses** and the `w(v)=1+λv²` objective is rejected. Two
corrections to earlier-session reasoning: (1) Step-1's "MSE retrain can't beat deployed" (cold 0.0376) was an
**initialization** artifact — cold `init_coset` sticks in a tail-light basin (~8.5% tail-share); warm-starting
from the deployed codebook escapes into the real-data optimum (~88% tail-share, KLD 0.0331). (2) The ~88%-tail
warm codebooks are **not degenerate** (the earlier λ=1 "degenerate" read was wrong) — real-27B whitened KV is
genuinely heavy-tailed, so plain MSE on it already resolves the tail; the synthetic-N(0,1) premise behind
tail-weighting was the error. 512 warm-refine (ws512_w01 0.037681) **cannot** beat deployed even warm-started →
the 1024 widen is necessary. **Ship candidate (PROVISIONAL): `real27b-1024-ws-w0.bin`** — pending the Confirmation below, which **reverses
this**.

**Confirmation (#524) — the win is SEED-LUCK, not robust; bake PAUSED.** The paired re-run re-certified the
instrument (deployed re-anchors **0.036648** exactly; ws1024_w0 reproduces **0.033130**; ws1024_w005 0.034034 —
no path/env/transcription error). But the decisive cell, a **seed=2 re-train of the exact winning recipe** (1024
widen, warm-start from deployed, MSE λ=0), landed at **0.037671 — WORSE than deployed**, despite a *lower*
held-in MSE (em 0.026003 vs seed=1's 0.026241). Across two independent seeds the same recipe gives KLD
{0.0331, 0.0377} — a 0.0046 spread that *straddles* deployed 0.0366 and exceeds the apparent −9.6% margin.
**MSE held-in distortion does NOT predict KLD** (seed=2 has the *better* MSE yet the *worse* KLD), so the
trainer's objective cannot be trusted to pick the KLD-good basin, and seed=1's win is within seed-induced
variance — not a transferable quality gain. **Verdict reversed: no robust symmetric-3.25 bpv codebook
improvement demonstrated; the bake is PAUSED.** seed=1's codebook genuinely beats deployed *on this corpus*,
but shipping it as "−9.6% better" would overclaim a corpus-specific lucky draw. Proper path (rebuild-free):
train N seeds, select best by KLD on a TRAIN corpus, **VALIDATE on a HELD-OUT corpus**, ship only if the win
transfers. The Step-3 asymmetric `_w` kernel work (the bit-allocation frontier) is codebook-independent and can
proceed separately.

| confirm cell | KLD | vs deployed | note |
|---|---|---|---|
| conf_deployed | 0.036648 | — | re-anchor, exact reproduction (instrument OK) |
| conf_ws1024_w0 (seed=1) | 0.033130 | −9.6% | reproduces bit-identically |
| conf_ws1024_w005 (seed=1) | 0.034034 | −7.1% | reproduces |
| **conf_ws1024_w0_s2 (seed=2)** | **0.037671** | **+2.8%** | **same recipe, worse than deployed → win is seed-luck** |

**Best-of-N + held-out validation (#524) — DEFINITIVE: the codebook win is train-corpus OVERFIT; deployed
generalises best.** Trained N=6 λ=0 warm-start seeds, measured each on the train corpus (wiki.test.mid) and on a
genuine HELD-OUT corpus (wiki.valid.mid, own 18 GB f16 base). Held-out deployed anchor = **0.045878**.

| seed | train-KLD | held-out KLD (deployed 0.045878) |
|---|---|---|
| s1 | 0.033130 (best on train) | 0.048497 (+5.7% — near-WORST on held-out) |
| s6 | 0.034048 | 0.050606 (worst) |
| s5 | 0.035175 | 0.045300 |
| s2 | 0.037671 | 0.045125 |
| s3 | 0.037959 (near-worst on train) | 0.044793 (BEST on held-out) |
| s4 | 0.038335 | 0.047197 |
| **mean** | 0.036053 (≈deployed) | **0.046920 — WORSE than deployed 0.045878** |

Train-KLD **anti-correlates** with held-out (Spearman ρ ≈ **−0.6**): selecting a codebook by train-KLD actively
picks the *worst*-generalising one. seed=1's "−9.6%" is **+5.7% worse** than deployed on held-out; the
retrained mean is worse than deployed on held-out. The apparent gain was pure overfit to the
activation-dump/eval-corpus distribution. **Verdict (FINAL): no robust, transferable symmetric-3.25 bpv codebook
improvement exists; the deployed (buun) codebook is near-optimal and generalises better than any real-27B
retrain. Ship deployed UNCHANGED — the codebook front is CLOSED.** The remaining "improve TCQ" lever is the
asymmetric bit-allocation frontier (Step 3, codebook-independent). Methodological lesson: a single-corpus KLD
"win" on a quant codebook is overfit-prone — ALWAYS held-out-validate before shipping (here it flipped a
−9.6% "win" into a +5.7% regression).

**Step 3 — asymmetric TCQ frontier (#525): K-dominance CONFIRMED (modest, transfers); asym = LINEAR (not
Pareto); wide-K `_w`-asym BUGGY + redundant.** Built the `turbo3_tcq_w`/`turbo2_tcq` FA-VEC instances (+ reverse)
+ both `both_tcq` predicates + codebook loaders (6 additive edits; dual-DSO byte-identical; 8 new `vec_case`
instances `nm`-verified). Frontier on TRAIN (wiki.test.mid) and HELD-OUT (wiki.valid.mid), baked codebooks:

| K / V | ~bpv | train KLD | held-out KLD |
|---|---|---|---|
| turbo2_tcq / turbo2_tcq | 2.25 | 0.070933 | 0.087088 |
| turbo2_tcq / turbo3_tcq (strong-V) | 2.75 | 0.056672 | 0.073838 |
| turbo3_tcq / turbo2_tcq (strong-K, #513) | 2.75 | 0.051501 | **0.066634** |
| turbo3_tcq / turbo3_tcq (deployed) | 3.25 | 0.036648 | 0.045878 |

(1) **K-dominance holds + transfers** — strong-K beats strong-V by ~10% on BOTH corpora (train 0.0515 vs 0.0567;
held-out 0.0666 vs 0.0738), confirming anbeeld's "K precision dominates the tail." (2) **But asym is NOT a Pareto
win** — the best 2.75-bpv point (strong-K) lands ~exactly on the linear 2.25↔3.25 interpolation (held-out interp
0.0665 vs measured 0.0666); strong-V sits *above* the line (strictly worse). So asym yields a valid intermediate
operating point (always strong-K orientation), not free quality. (3) **The NEW wide-K `_w`-asym is BROKEN** —
KLD 1.214 (train) / 1.296 (held-out), byte-identical with/without a real 1024-codebook override → decode-LOGIC
bug (reads the wrong codebook symbol/size for the mixed-width pair), NOT seeding (bug-629). Symmetric `_w` with
the baked placeholder works (0.037125 ≈ deployed turbo3 0.0366). (4) **`_w` is redundant anyway** — 1024-state ≈
512-state quality (symmetric `_w` 0.0371 ≈ turbo3 0.0366; consistent with the best-of-N codebook-overfit
finding), so a *fixed* `_w`-asym would merely reproduce `turbo3/turbo2` (0.0666) — no gain over the existing
#513 asym. **Verdict (FINAL, across all three "improve TCQ" avenues): the deployed `turbo3_tcq` (symmetric) +
existing `turbo3_tcq/turbo2_tcq` asym (#513) are ALREADY at the TCQ frontier; none of {codebook retrain, free
state-widen, wide-K asym} beats it. The wide-K `_w`-asym instances (#525) are buggy + redundant → revert (or
gate off) — only the explicit opt-in `-ctk turbo3_tcq_w -ctv turbo2_tcq` combo is affected; the default/shipped
TCQ paths are untouched and validated.**

### 5a-TCQ-RULER. Primary-target quality-in-use (Gemma-4-A4B, #447/#501)

The 27B PPL/KLD above is **head_dim 128**; the actual primary target is **Gemma-4-A4B**
(head_dim 256/512). The PPL/KLD instrument was finally pointed at it on 2026-06-21 and found
**INVALID on these Gemma merges** (q8_0 control Same-top 68% — see §5a-TCQ-A4B-KLD below); so the
primary-target evidence rests on RULER, not PPL. RULER retrieval, forced
`KVTYPE_OVERRIDE=turbo3_tcq` (ours-only), model `gemma-4-A4B-98e-v6-coder-it-Q4_K_M`, 5 samples
(256k cell = 1), `niah_single_1` (decisive needle metric) + `vt` (NS=5-noisy):

| task | 4k | 32k | 256k |
|---|---|---|---|
| `niah_single_1` | **100%** | **100%** | **100%** (measured — see below) |
| `vt` | 100% | 60% (noisy) | — (skipped) |

`niah_single_1` is clean at every context: turbo3_tcq's trellis decode holds the needle on Gemma's
head_dim 256/512 with **zero degradation vs cached vanilla** (vanilla niah=100 at all ctx). `vt`@32k=60%
is within the cached-vanilla noisy band (vt 60–80, NS=5 task), not a regression — `niah` is the correctness
signal.

**The 256k cell is a measured 100%, and its story is a clean throughput-vs-correctness separation
(bug-594).** At the harness default `--http-timeout 1200`, niah@256k scored **0%** — but every sample hit
the read-timeout mid-prefill (steady monotonic prompt-processing, server healthy, clean cancel), because
turbo3_tcq is **always-fuse / resident in-register** (KV fit in ~17 GiB) and *cannot* ride the f16
streaming/dequant-on-lift path — so its prefill runs ~25→8 tps (O(n²)) where f16-streaming did the whole
256k cell in 1208 s. Re-running one sample at `--http-timeout 36000` (the `HTTP_TIMEOUT` env added to
`run-baseline.sh`) → **100%**, with the gold needle `5663623` exactly recovered as completion `' 5663623.'`,
`gen_secs=20879` (~5.8 h prefill). So the 256k decode is **byte-correct, just throughput-bound in-register**;
the perf cliff was the #505 gap — the f16 trellis dequant-on-lift now **exists** (#533: `turbo{3,2}_tcq→f16`,
verified composing under DCA 2026-06-30), so the prefill MMA-materialize path is available; a fresh 256k
wall-time re-measure on the post-#533 DSO is deferred (optional). Do **not** read a 256k turbo3_tcq 0% as a
trellis bug — check `samples.jsonl` `reason` for `ReadTimeout` first.

**Trellis code review (#447, collaborative gate).** The Viterbi right-shift trellis was traced
end-to-end and is algebraically correct (state `ns=(prev>>k)|(out<<6)`, free initial state, 6-init-bit +
128×k-bit packing ⇄ decoder window at `bit_pos=t*k`); encode↔decode codebooks verified byte-identical
(512 + 256 vals); V-alpha applied once (encode-baked, decode symbol inert); launcher/bt-buffer sound; the
non-FA GET_ROWS dequant is dead code. Two latent footguns logged (not live bugs): **`TURBO_TCQ_CB`
overrides only the encode codebook, not the decode `_fattn` copy** (asymmetric — custom-codebook runs
would corrupt); and **K/V split is stringly-typed on `strncmp(dst->name,"cache_k_",8)`** (an upstream
KV-tensor rename would silently flip K-alpha onto V). Both are cheap one-line hardenings, deferred.

**TCQ gate verdict:** correct **and** quality-validated on the primary target — shippable on
Gemma-4-A4B/27B-class. Resident contexts (≤~32k) are correct *and* fast; 256k is correct, and the prefill
MMA-materialize that removes the in-register O(n²) cliff now exists (#533, the #505 lift) — a 256k wall-time
re-measure is the only deferred item.

> **WS2 update (#629, DEFAULT-ON).** The in-register decode throughput above is now superseded for
> the DCA-on serving path by the WS2 turbo-V in-register kernel: the relevant A4B tcq @256k decode
> numbers are now the **§5x** WS2 cells (A4B turbo3_tcq **64.5 tps**, turbo2_tcq **66.8 tps**;
> +72% / +68% vs the f16-lift ref), each niah 100 + logit-lossless (`real_frac 0`). Read the §5x
> tcq rows, not the pre-WS2 in-register figures, for current turbo3_tcq/turbo2_tcq decode-in-use.

### 5a-TCQ-A4B-KLD. PPL/KLD instrument is INVALID on Gemma-4-A4B merges (#447, bug-631)

The deferred "quantitative KLD on the primary target" cell was finally run (2026-06-21, RTX 3090,
`perplexity` host build, `google_gemma-4-26B-A4B-it-Q4_K_M`, wiki.test.mid 320 KB, ctx 2048, f16
KLD-base, InnerQ OFF, `TURBO_TCQ_ALPHA_V=1.0`). It does **not** produce usable numbers, and the
**q8_0 near-lossless control proves why**:

| KV tier | Mean KLD | Same-top p | (expected on a sane instrument) |
|---|---|---|---|
| q8_0 (near-lossless **control**) | 0.957 | **68.3%** | ~0.02 / ~99% |
| q6_0 | 1.080 | 66.5% | — |
| turbo3_tcq (deployed) | 2.264 | 51.2% | — |

The **f16 base itself scores PPL ≈ 43910** on raw wikitext (vs the 27B general-merge's **6.69** on
the *same* harness — proving the harness is fine, the model isn't). These omnimerge coder/instruct
Gemma-4 GGUFs sit in a **near-uniform high-entropy regime** on prose (CE ≈ 10.7 nats out of a 256k
vocab's 12.45 nats ceiling): the top token is barely separated from the runner-up, so **Mean-KLD is
amplified** (a near-flat reference yields large KL for any perturbation) and **Same-top is unstable**
(argmax is coin-flippy even under q8_0's near-zero noise → 68%, not 99%). Both metrics here measure
**distribution flatness, not quant fidelity.** Ruled out as causes: flash-attn/iSWA (FA on==off, both
garbage), the specific GGUF (google-official *and* the RULER-validated v6-coder both garbage — v6
worse at 142410), and BOS (`--override-kv tokenizer.ggml.add_bos_token=bool:true` left f16 PPL
**byte-identical** to 6 decimals). The tier *ordering* is still sane (turbo3_tcq 51.2 < q6_0 66.5 <
q8_0 68.3 same-top — lower-bit = noisier), so the instrument is non-random, merely **absolute-invalid**.

**Methodology rule (load-bearing):** the **q8_0 (near-lossless) control is the validity gate for any
KLD/same-top harness** — if q8_0 Same-top isn't ~99% (or KLD isn't ~0.02), the model/corpus is in a
bad regime and *every* number from that run is meaningless; abort and switch instrument. This is
exactly *why* opencoti validates Gemma KV-quant via **RULER niah** (high-confidence needle tokens,
immune to the flat-distribution instability — niah=100% above), never PPL. The quantitative TCQ-fidelity
evidence remains the **27B head_dim-128** KLD (§5a-TCQ-27B). No primary-target *fidelity* number can be
drawn from PPL; the primary-target *correctness* claim stands on RULER. The 18 GB garbage f16 base was
deleted (reclaimable); cell logs kept as evidence (`.opencoti/ppl-kld/a4b_a4b_*.log`).

### 5a-TCQ-FP64. Encode precision — fp64-selectable Viterbi (#447/#506, `TURBO_TCQ_FP64`)

The buun trellis encodes in fp32 end-to-end. Because a Viterbi trellis is a chaotic system — fp precision
can flip which path wins at near-tie costs — we added a **compile-time fp64 accumulator path** for the
*encode* Viterbi (`k_set_rows_turbo{3,2}_tcq` templated on `acc_t`; env `TURBO_TCQ_FP64=1` dispatches the
`double` instantiation). Decode stays fp32 (it reads stored integer states; fp64 on the FA hot path = ~1/64
throughput for ~zero quality). The point was not a guaranteed win but a **measurement**: is the fp32 trellis
leaving quality on the table at the path-selection margin? Same 8B instrument (Qwen3-8B-Q8, wiki,
ctx2048/chunk1024, `TURBO_TCQ_ALPHA_V=1.0`), fp64 DSO.

| tier | KLD fp32 | KLD fp64 | Δ | PPL(Q) fp32→fp64 | sametop% fp32→fp64 |
|---|---|---|---|---|---|
| turbo3_tcq | 0.200389 | 0.204047 | **+0.0037 (+1.8%)** | 10.306 → 10.212 | 82.99 → 82.76 |
| turbo2_tcq | 5.215325 | 5.258573 | **+0.0432** | 1113 → 1154 | 18.61 → 18.83 |

Two clean conclusions. **(1) fp32 is byte-faithful and the templating is inert.** With `TURBO_TCQ_FP64`
unset, the rebuilt DSO reproduces the §5a-TCQ matrix to **all six decimals** (turbo3_tcq 0.200389,
turbo2_tcq 5.215325) *and* the turbo8/4/3/2 controls bit-identical — `acc_t=float` is the default, so every
existing launch resolves to the original kernel (byte-identity by construction, confirmed by measurement).
**(2) fp64 changes the path but does not improve quality — it marginally *regresses* KLD.** The fp64 encode
is the true MSE-optimal Viterbi path in the FWHT-whitened domain, but **MSE-optimal ≠ KLD-optimal**:
minimizing squared reconstruction error is a proxy, and fp32's rounding happens to land on paths a hair
*better* on the downstream whole-distribution metric. The shift is real and measurable (sametop moves
~0.2 pp, KLD ~2% on turbo3_tcq) — confirming the trellis *is* precision-sensitive at the margin — but it is
in the non-improving direction. Critically, fp64 KLD stays in-regime (0.204, no catastrophe), proving the
fp32 decode reads fp64-encoded symbols correctly (no encode↔decode break).

**Verdict:** **fp32 is confirmed sufficient** and remains the default (byte-faithful to buun).
`TURBO_TCQ_FP64` is retained as an **opt-in audit oracle** — the canonical "true optimal path" reference for
the precision-sensitivity question — not a quality lever; do not enable it for production. (`fmad` left at
its default: fp64 FMA is *more* accurate via single rounding, the opposite of the chaotic-SDM bit-repro case
where `--fmad=false` matters. Matrices: `.opencoti/ppl-kld/tcq-matrix-fp32.tsv` / `-fp64.tsv`.)

**Decode V-accumulator precision (#547) — closed as moot, F32 is sufficient (2026-06-30).** #547 proposed an
fp32/fp64 lever for the *decode-side* V accumulator (distinct from the encode Viterbi above), premised on
long-ctx accumulation drift pairing with sparse-V. Three facts close it without a build: (1) the FA-VEC
decode V accumulator is **already F32** (`float2 VKQ`, `fattn-vec.cuh:207`; `KQ_sum` is `float`), not f16 —
there is no precision to recover by going fp32, and online-softmax rescales per tile so the combine is
length-stable by construction; (2) F32 accumulation is **already proven correct at 256k** — turbo3_tcq (the
most aggressive tier) holds the needle exactly, niah=100 at 256k (§5a-TCQ-RULER), with no observed drift;
(3) the motivating premise ("pairs with sparse-V at long ctx") **dissolved** — sparse-V is an iSWA-only win
(#546) whose global V-cache is *bounded* (≤1536-cell window class), so accumulation depth does not grow with
ctx where sparse-V actually runs. An fp64 decode accumulator would cost ~1/64 throughput on the FA hot path
for **zero** measured correctness gain. Not built; **closed as F32-sufficient**.

### 5a-TCQ-ENC. Encode throughput — warp-synchronous Viterbi (#533/#538, solidpc RTX 3090)

The TCQ encode (`k_set_rows_turbo{3,2}_tcq`) runs as a **separate kernel on every KV write** — once per
prompt group at prefill, once per token at decode — so its cost lands directly on prefill tps. ncu on the
original 512-thread/`__syncthreads` design (`k_set_rows_turbo3_tcq`, DSO `e9e7f864`) found it
**latency-bound on the 128-step block-barrier chain**: SM throughput 25%, **DRAM 0.1%**, occupancy 33%,
39 µs/launch — neither compute- nor memory-bound, just stalling at barriers in lockstep (16 warps hit each
of 128 `__syncthreads` together; ~3 blocks/SM ⇒ SM idle ~75%). That is exactly why the earlier #538
register/warp-shuffle pass (occupancy + bank-conflict tuning) moved nothing (−3.6%): the kernel was never
occupancy- or memory-bound.

**Fix (#533):** collapse each 128-element group from a 512-/256-thread block to **one 32-thread warp**
(turbo3: 16 states/lane; turbo2: 8 states/lane). The contiguous state→lane map makes each trellis group's
predecessors fall entirely within one lane, so the per-step predecessor-min is **thread-local** (no
shuffle); a 64-entry per-warp smem broadcast under `__syncwarp` replaces the block barrier; the backtrace
moves to global (frees smem for occupancy). `TCQ{3,2}_WPB=8` warps/block run at *different* DP steps
instead of in lockstep, hiding the per-group serial latency. **Zero `__syncthreads`** in the new kernel
(ptxas-confirmed). Reuses #538's warp-shuffle min primitive as the building block.

Validated **byte-equivalent offline before the rebuild**: the round-trip harness
(`.opencoti/tcq-warp-enc-full.cu`, decode(encode(x)) vs the WHT reference on 4096 random-Gaussian groups)
gives the warp encode cosine **1.00000 vs the old 512-thread design** (full encode **3.74×**; the DP alone
**7.09×**).

**Prefill tps (A4B Q4_K_M, ~3682-tok prompt, `m536-prefill-tps.sh`):**

| tier | old (#538, `e9e7f864`) | warp (#533, `4644b66a`) | Δ |
|---|---|---|---|
| f16 (shield) | 2263 | 2296 | +1.5% (parity) |
| scalar_q8 (shield) | 2550 | 2532 | parity (run noise) |
| turbo3 non-TCQ (shield) | 2541 | 2520 | parity |
| **turbo3_tcq** | **1421** | **2189** | **+54% (+768 tps)** |
| **turbo2_tcq** | **1928** | **2283** | **+18.5% (+355 tps)** |

(Both warp tiers landed in one DSO `4644b66a`; turbo3_tcq held 2189 byte-stable across the turbo3-only
`9ef13bdc` and the turbo2-build `4644b66a`, confirming the turbo2 source change is isolated.) turbo3_tcq
recovers the entire #534–536-era regression (1456→1421) **and** the historical 1798 mark, landing within
~13% of the turbo3 non-TCQ ceiling (2536) — the residual is the encode work that remains (now ~3.7×
cheaper), not barrier stall. turbo2_tcq, lighter at 256 states, lands *above* turbo3_tcq at 2283 (~9% off
the ceiling). f16/turbo3 unchanged confirm no collateral regression. Both warp encodes clock ~3.75×
offline (256-/512-thread → warp: turbo2 0.895→0.239 ms; turbo3 likewise).

**Correctness — turbo3_tcq (live, `m533-kld-gate.sh`, Qwen3-8B-Q8, ctx2048, DSO `4644b66a`):** turbo3_tcq‖f16
KLD **0.186** (Same-top 84%), matz‖fused 0.058, regression-shield plain-turbo3‖f16 0.350 — all in the
expected class, no regime change. Consistent with the offline byte-equivalence: the Viterbi path and stored
symbols are **identical** to the old 512-thread design (decode cosine 1.00000); only the norm/recon
reductions reorder at the ~1e-7 fp level, so quality is unchanged by construction. (The 0.186 here vs the
§5a-TCQ-FP64 matrix's 0.200389 is a harness-config difference — gate corpus/chunking — not an encode change;
the gate is internally A/B-consistent.)

**Correctness — turbo2_tcq (offline round-trip + live):** turbo2 is **fidelity-equivalent but not
byte-identical** to the 256-thread reference. The offline harness (`.opencoti/tcq-warp-enc-t2.cu`, 4096
Gaussian groups, decode(encode) vs WHT-ref) gives the warp encode mean cosine **0.96002** (min 0.944) vs the
256-thread reference's **0.95989** (min 0.935) — equal quantization fidelity — while warp-vs-256 decode
cosine is 0.998969 with **7.2% of groups choosing a different path**. Those differences are **benign
tie-break convention**, not suboptimality: turbo2 is 2-bit/256-state (coarse ⇒ frequent exact cost-ties),
and the warp argmin breaks ties by lowest-index where the 256-thread reduction breaks them by shuffle-order;
both land on *equally* MSE-optimal paths (proven by the identical mean fidelity, and the warp's worst case
0.944 ≥ the reference's 0.935). turbo3 showed ~0% path divergence because 3-bit/512-state has far fewer ties.

**Real-target regression gate (decisive, `m533-27b-tcq-regress.sh`, Qwen3.6-27B, ctx2048, vs cached
`base_f16_27b.dat`):** on the model where turbo2_tcq is *usable*, the warp encode shows **no quality
regression** — turbo2_tcq‖f16 KLD **0.069940** vs the documented old-encode baseline **0.070933** (Δ −0.001,
marginally *better*), Same-top **92.65** vs 92.67. The in-run control turbo3_tcq lands KLD 0.034606 / Same-top
95.54 with **PPL(base) = 6.297831 exact**, confirming the instrument (base+model+corpus+env all correct). So
the tie-break path differences provably **do not perturb a real-model distribution** — exactly as expected
(27B is not a chaotic regime). The live **8B** KLD did move within-regime (turbo2_tcq‖f16 5.48→5.29,
Same-top ~21%), but 8B turbo2 is a garbage regime (unusable either way); that shift is two equally-valid
quantizations diverging where it doesn't matter, *not* a regression — the 27B gate is the one that counts,
and it passes. (turbo3_tcq's 27B KLD differs −0.002 from its Jun-19 baseline; that is **not** the warp encode
— byte-identical, 8B KLD 0.185718 identical across both warp DSOs — but the cumulative #534–537 decode
smem-codebook ports that postdate that baseline; both tiers landing slightly better is consistent with them.)

Both warp encodes are a **pure throughput optimization**. Source lives in `turbo-tcq-cuda.cuh` +
`set-rows.cu` (additive; bt always global, `use_shared_bt` ignored; `acc_t` fp64 path preserved).

### 5a-TCQ-DEC. Decode throughput in use — turbo3_tcq × MTP (#553, A4B v6-coder Q4_K_M, solidpc, 2026-06-24)

The shippable decode story for the extreme tier is **turbo3_tcq + assistant-MTP**. Measured on coherent
in-domain output (chat coding prompt, `/v1/chat/completions`, `--temp 0`, 256 gen tok, graphs default,
`coherent-mtp.sh`):

| KV tier | decode tok/s (MTP-off) | decode tok/s (MTP-on) | MTP gain | draft acceptance |
|---|--:|--:|--:|--:|
| f16 | 88.95 | 112.37 | +26% | 0.787 |
| turbo3 | 69.66 | 94.44 | +36% | 0.827 |
| **turbo3_tcq** | 56.63 | **75.63** | **+34%** | 0.652 |

MTP is the largest single decode-tps lever for turbo3_tcq (mtp.md §3.0/§3.0a), and it composes with CUDA
graphs (graphs survive turbo3_tcq + sparse-V: +13.4% / +13.1% on the current DSO, matching decode-levers L6).
The single-prompt turbo3_tcq acceptance (0.65) is **prompt noise, not a deficit**: over 3 diverse coherent
prompts (`coherent-mtp-multi.sh`) the means are f16 0.745 / turbo3 0.757 / **turbo3_tcq 0.703** (~0.05 spread,
within each tier's own variance; turbo3_tcq even beat turbo3+f16 on one prompt). No spec bug — turbo3_tcq is
the *more* accurate tier (KLD 0.0346 < turbo3 0.047, §5a-TCQ-27B).

> ⚠️ **Measure decode-tps/acceptance on coherent output only.** An instruction-less prompt (raw RULER/WikiText
> haystack → `/completion`) collapses greedy decode into degenerate repetition where acceptance is meaningless
> noise and even f16 shows greedy MTP-off ≠ MTP-on. An earlier haystack sweep mis-read turbo3_tcq acceptance
> at 0.25 / "MTP hurts turbo" — a harness artifact (bug-710), *not* a TCQ kernel/codebook bug; turbo3_tcq is
> the more accurate tier (§5a-TCQ-27B, KLD 0.0346 < turbo3 0.047) and cannot legitimately accept worse.
> Gemma-4 thinking-coder writes generation to `choices[0].message.reasoning_content` (`.content` is empty).
> Latent: `TURBO_TCQ_CB` override reaches only the FA-VEC `__constant__`, not the MMA-lift copy
> (`d_turbo3_tcq_cb_cpy`); harmless by default (baked tables byte-identical) but would split draft/verify
> decode during an A′ codebook sweep.

### 5b. Validated-tier full matrix — size · fidelity · throughput · quality (#529, cross-instrument)

The comprehensive scalar-vs-turbo, symmetric-vs-asymmetric comparison on the **shippable** tiers, post
`turbo3_tcq_w` removal (#527, DSO sha `7f769e1d`). Two instruments by necessity (see §5a-TCQ-A4B-KLD /
#528): **fidelity = PPL/KLD on Qwen3.6-27B** (head_dim 128, the only valid KLD instrument — Gemma-4-A4B
raw-PPL is ~44k garbage), **quality-in-use = RULER niah on Gemma-4-A4B-98e-v6-coder** (the deployed
primary target). tps on both. **DCA split only where it bites (32k+):** DCA is ~inert at short ctx, and
**TCQ tiers now compose under DCA (as of #533; was rc=134 pre-#533, verified 2026-06-30)** — the #533
`turbo_tcq→f16` lift gives DCA's `dca_lift_to_f16` a path, so DCA
(which needs the lift) cannot compose; scalar + non-TCQ-turbo compose via the #446 lift. 256k/512k RULER
deferred to **bs2** (Blackwell) per plan. _Status: **#529 COMPLETE** — size · noDCA fidelity · throughput
(27B+A4B) · RULER niah all LIVE on the all-quants GPU FA-VEC DSO (#531). DCA-fidelity column is n/a on the
`perplexity` instrument (server-only flag, ⁴); DCA composition proven server-side (#444) + §1. 256k/512k
RULER → bs2._

> **WS2 DCA-on throughput column (#629).** The throughput numbers in this matrix are the **noDCA
> in-register / f16-lift** decode path. For the **DCA-on @256k** serving path the shippable turbo/TCQ
> tiers now decode via the WS2 in-register turbo-V kernel (**DEFAULT-ON**), a **+68–95%** decode win
> over the f16-lift ref, retrieval-lossless (niah 100) — see **§5x** for the full D512 (A4B/31B) +
> D256 (omni27/qw35a3) matrix. In-register turbo/TCQ-V is a decode WIN with DCA-on at long ctx, the
> opposite of the noDCA short-ctx "turbo costs decode vs scalar" floor (§5a-TCQ-DEC, decode-levers.md).

**Size — bytes/value (KV stored size, both K and V) vs f16.** Analytical from block layout; asymmetric =
mean(K,V).

| config | ctk/ctv | bpv | size vs f16 |
|--------|---------|-----|-------------|
| f16 (ref)            | f16/f16              | 16.0 | 100 %  |
| q8_0                 | q8_0/q8_0            | 8.5  | 53.1 % |
| q6_0                 | q6_0/q6_0            | 6.5  | 40.6 % |
| q5_0                 | q5_0/q5_0            | 5.5  | 34.4 % |
| q4_0                 | q4_0/q4_0            | 4.5  | 28.1 % |
| q8_0K / q6_0V (asym) | q8_0/q6_0            | 7.5  | 46.9 % |
| q5_0K / q4_0V (asym) | q5_0/q4_0            | 5.0  | 31.3 % |
| turbo3_tcq           | turbo3_tcq/turbo3_tcq | 3.25 | 20.3 % |
| turbo2_tcq           | turbo2_tcq/turbo2_tcq | 2.25 | 14.1 % |
| t3tcqK / t2tcqV (asym) | turbo3_tcq/turbo2_tcq | 2.75 | 17.2 % |
| t2tcqK / t3tcqV (asym) | turbo2_tcq/turbo3_tcq | 2.75 | 17.2 % |

**Fidelity — Qwen3.6-27B, full-vocab PPL + KLD vs cached f16 base** (`perplexity` host build, ctx 2048,
`wiki.test.mid.raw`, `base_f16_27b.dat`; f16 ref PPL 6.298). KLD↓, Same-top↑. **DCA column n/a on this
instrument⁴** — the `perplexity` tool has no `--dca` flag (DCA is server-only); composition with quantized KV
is proven server-side, not via full-vocab KLD. TCQ now composes under DCA (as of #533); its DCA-KLD value
remains server-only by the instrument limitation (not a TCQ block).

| config | ctk/ctv | PPL(Q) | KLD noDCA | top% noDCA | KLD DCA | top% DCA |
|--------|---------|--------|-----------|------------|---------|----------|
| q8_0                 | q8_0/q8_0   | 6.313 | 0.01760 | 97.66 | n/a⁴ | n/a⁴ |
| q6_0                 | q6_0/q6_0   | 6.310 | 0.01965 | 97.68 | n/a⁴ | n/a⁴ |
| q5_0                 | q5_0/q5_0   | 6.291 | 0.01973 | 97.46 | n/a⁴ | n/a⁴ |
| q4_0                 | q4_0/q4_0   | 6.334 | 0.02505 | 96.85 | n/a⁴ | n/a⁴ |
| q8_0K / q6_0V (asym) | q8_0/q6_0   | 6.319 | **0.01680** | 97.63 | n/a⁴ | n/a⁴ |
| q5_0K / q4_0V (asym) | q5_0/q4_0   | 6.310 | 0.02424 | 97.09 | n/a⁴ | n/a⁴ |
| turbo3_tcq           | t3tcq/t3tcq | 6.389 | 0.03665 | 95.64 | composes (#533) | composes (#533) |
| turbo2_tcq           | t2tcq/t2tcq | 6.456 | 0.07093 | 92.67 | composes (#533) | composes (#533) |
| t3tcqK / t2tcqV (asym)| t3tcq/t2tcq | 6.431 | 0.05150 | 93.81 | composes (#533) | composes (#533) |
| t2tcqK / t3tcqV (asym)| t2tcq/t3tcq | 6.346 | 0.05667 | 94.02 | composes (#533) | composes (#533) |

⁴ **`perplexity` rejects `--dca` (`error: invalid argument: --dca`) — DCA is a server-only flag**, so a
full-vocab DCA-on KLD column is not obtainable on this instrument (the attempted sweep, `s5b-dca-fidelity.sh`,
failed at arg-parse on all cells — no GPU time spent). DCA's quantized-KV composition is instead proven on the
**server path**: the m444 gate's teacher-forced logit-equivalence (f16-DCA vs q8-DCA, `real_frac=0`, #444) and
the §1 RULER-VT 256k→1M cells (all DCA-on, scored 0.876–0.984). Scalar/asym compose via the #444 f16-lift;
**TCQ now composes under DCA (as of #533; was rc=134 pre-#533, verified 2026-06-30)**. The takeaway the column would have shown — *DCA does not degrade
quantized-KV fidelity* — is the server-side evidence above, not a perplexity number.

**Note (#531 — RESOLVED, the all-quants FA-VEC default).** Earlier the production CUDA DSO was built with
`FA_ALL_QUANTS=0` (cuda.sh default), so `collect_gpu_sources` compiled only the 4 minimal fattn-vec instances
(f16/q4_0/q8_0/bf16) + the q6_0 hook, and the dispatch block for q5_0/q5_1/all asymmetric pairs was `#ifdef`'d
out — `q5_0`/`q5_0` had no native GPU FA-VEC kernel and silently fell back to CPU-FA (a 568 %-CPU crawl that
timed out the perplexity cell, and would have crawled every RULER/tps cell). **Fixed, not papered over:**
`GGML_CUDA_FA_ALL_QUANTS` is now the shipped default (`build-pipeline.ts` forwards `--fa-all-quants` to the
cuda backend), so every scalar K/V combo (q5_0, q5_1, q6_0, all symmetric **and** asymmetric) compiles a
native GPU FA-VEC kernel — **no KV tier falls back to CPU-FA.** The all-quants DSO was installed into both
side-load paths (`~/.llamafile/v/<ver>/ggml-cuda.so` + `vendors/dist/.../<ver>/ggml-cuda.so`, byte-identical;
`<ver>` resolved by `scripts/llamafile-version.sh`, never hardcoded — bug-635). No KV type is preferred over
another on GPU-path grounds; all run GPU FA-VEC (or, at long ctx, GPU FA-VEC under DCA). Every cell in this
§5b — q5_0 fidelity, all throughput, all RULER — was (re-)measured on this DSO; the q8_0_q6_0 RULER cell went
from a ~2 h CPU-FA crawl to ~30 s GPU FA-VEC, confirming the fix end-to-end.

**Throughput — decode/prefill tps** (server `/completion` timings, ctx 4096, `ignore_eos`; pp = prefill,
tg = generation; all GPU FA-VEC on the all-quants DSO, #531).

| config | ctk/ctv | 27B pp | 27B tg | A4B pp | A4B tg |
|--------|---------|--------|--------|--------|--------|
| f16 (ref)             | f16/f16     | 911 | 22.5 | 2462 | 73.1 |
| q8_0                  | q8_0/q8_0   | 919 | 22.2 | 2558 | 69.1 |
| q6_0                  | q6_0/q6_0   | 927 | 22.0 | 2579 | 67.4 |
| q5_0                  | q5_0/q5_0   | 920 | 22.0 | 2624 | 68.0 |
| q4_0                  | q4_0/q4_0   | 929 | 22.2 | 2684 | 70.1 |
| q8_0K / q6_0V (asym)  | q8_0/q6_0   | 922 | 22.2 | 2565 | 68.2 |
| q5_0K / q4_0V (asym)  | q5_0/q4_0   | 923 | 22.2 | 2635 | 69.8 |
| turbo3_tcq            | t3tcq/t3tcq | 357 | 18.9 | 373  | 39.1 |
| turbo2_tcq            | t2tcq/t2tcq | 382 | 19.3 | 424  | 41.1 |
| t3tcqK / t2tcqV (asym)| t3tcq/t2tcq | 277 | 18.4 | 270  | 36.1 |
| t2tcqK / t3tcqV (asym)| t2tcq/t3tcq | 279 | 18.4 | 266  | 36.3 |

**Reading (throughput).** Among **scalar** tiers, KV-quant type is throughput-neutral: 27B clusters at
~920 pp / ~22 tg, A4B at ~2460–2680 pp / ~67–73 tg regardless of K/V width — the decode is weight-bound,
not KV-bound, so picking q4_0 over q8_0 buys size, not speed. **TCQ pays a decode tax** (in-register
Viterbi codebook lookup, #389): on the big 27B it is mild (~15 % slower tg, ~2.5× slower pp — the model is
weight-bound, so KV-decode overhead is a small fraction of the per-token cost); on the small fast A4B it is
steep (~45 % slower tg, ~6× slower pp — here KV-decode is a large fraction). So **TCQ's 3–14 %-of-f16 size
win costs the most throughput exactly where the model is cheapest** — the size/speed trade is real and
model-size-dependent. Provenance: `.opencoti/ppl-kld/s5b-tps-{27B,A4B}.tsv`.
**— noDCA / short-ctx (ctx 4096) only.** This decode tax is the f16-lift path at short context; **with
DCA-on at long ctx (@256k) the WS2 in-register turbo-V path is a decode WIN (+68–95%)** — the turbo/TCQ
tier decodes *faster* than the f16-lift ref, not slower. See **§5x**.

**Quality-in-use — RULER niah_single_1, Gemma-4-A4B-98e-v6-coder** (% correct, 8 samples; all GPU FA-VEC
on the all-quants DSO, #531). 256k/512k measured on bs2 Blackwell, DCA-on `--dca-chunk-size 32768`,
5 samples each (#575, 2026-06-30).

| config | ctk/ctv | niah 4k | niah 32k | 32k DCA | 256k (bs2) | 512k (bs2) |
|--------|---------|---------|----------|---------|------------|------------|
| f16 (ref)             | f16/f16     | 100 | 100 | ≈noDCA² | 100 | 100 |
| q8_0                  | q8_0/q8_0   | 100 | 100 | ≈noDCA² | 100 | 100 |
| q6_0                  | q6_0/q6_0   | 100 | 100 | ≈noDCA² | 100 | 100 |
| q4_0                  | q4_0/q4_0   | 100 | —³  | ≈noDCA² | 100 | 100 |
| q8_0K / q6_0V (asym)  | q8_0/q6_0   | 100 | 100 | ≈noDCA² | 100 | 100 |
| turbo3_tcq            | t3tcq/t3tcq | 100 | 100 | composes (#533) | 100 | 100 |
| turbo2_tcq            | t2tcq/t2tcq | 100 | —³  | composes (#533) | 100 | 100 |
| t3tcqK / t2tcqV (asym)| t3tcq/t2tcq | 100 | —³  | composes (#533) | 100 | **80**⁴ |

² **32k-DCA niah was not separately run; `≈noDCA` is by inertness, not a fresh measurement.** At 32k (within
the model's effective window — noDCA niah is already saturated at 100), DCA's position-remapping is ~identity,
so DCA-on niah ≈ the noDCA cell. DCA's *measured* effect on KV-quant quality is the long-context story:
the canonical DCA-on retrieval evidence is §1 (RULER-VT 256k → 1M, all DCA-on, scored 0.876–0.984) and the
bs2 256k/512k niah cells above (every tier 100, save the 2-bit-V asym at 512k = 80, ⁴). Scalar/asym tiers compose with DCA via the #444 f16-lift (m444 gate
`real_frac=0`); **TCQ now composes under DCA (as of #533, the #505 lift; bs2 256k/512k niah filled above, #575)**. ³ 32k cell run only for
the symmetric-scalar and headline-TCQ tiers (q4_0 and the asym/secondary-TCQ tiers swept at 4k to bound the
matrix; 32k niah is saturated at 100 for every tier that was run, so the omitted 32k cells are not in doubt).
⁴ **t3tcqK/t2tcqV asym is the only non-100 cell — niah 80 at 512k (still 100 at 256k).** This is the same
tier §9's #444 all-KV matrix flagged as the lone DCA-sensitive case (turbo3_tcq/turbo2_tcq asym, 318→173
on the count-up task): a weak 2-bit-V tier pushed over by DCA's harder positional task at 2× native ctx.
It is an **intrinsic 2-bit-V quality floor at extreme ctx, not a DCA correctness bug** — the symmetric
turbo2_tcq holds 100 at 512k, and every symmetric/scalar tier is 100 at both depths. Boot was clean (no
SRV-FAIL); the cell ran full 5 samples. Recommendation: don't pair a 2-bit V with a 3-bit K beyond native
ctx; use symmetric turbo2_tcq or q8_0K/q6_0V instead.

> **SUPERSEDED (2026-07-10, bug-2118 + bug-2141).** This whole ⁴ reading is invalid: these #575
> cells ran with `--dca on` while bug-2118 made DCA a silent **no-op** on Gemma, so the "80 at 512k
> / 100 at 256k" was DCA-**off**, and the "intrinsic 2-bit-V floor" framing is wrong. On the fixed
> WS2 binary with **genuine** DCA (§12 Tranche 3b), the truth inverts: asym `turbo3_tcq`-K/`turbo2_tcq`-V
> is **20 at 256k (4/5 empty, broken forward)** and **100 at 512k** — a geometry-dependent NaN in the
> WS2 in-register-V + `wht_o` path (**bug-2141**), NOT a 2-bit-V quality floor (symmetric turbo2_tcq
> holds 100 at both depths, and `WS2_DCA_TURBO_V=0` recovers the asym cell to 100/0-empty). See
> §12 Tranche 3b + `.wolf/buglog.json` bug-2141. The symmetric-tier recommendation still stands, but
> for the *right* reason (quarantine asym turbo_tcq K≠V until the NaN-safe fix, not tier quality).

**Reading (fidelity).** Asymmetric **q8_0K/q6_0V is the standout — KLD 0.0168, the best non-q8 cell, at
46.9 % size** (K-precision dominates; cheap V). The TCQ ladder holds its published order (turbo3_tcq 0.0366 <
asym 0.051–0.057 < turbo2_tcq 0.071) at **3–14 %** of f16 — far smaller than any scalar, the
extreme-compression frontier. Scalars cluster tight: `q8_0` 0.0176 / `q6_0` 0.0197 / **`q5_0` 0.0197** (top
97.5 %) / `q4_0` 0.0251 (top 96.8 %) — a smooth 8→5→4-bit ladder, every cell GPU FA-VEC. **noDCA fidelity is
now 10/10** (the `q5_0`-symmetric cell, formerly a CPU-FA timeout, landed at KLD 0.0197 on the all-quants DSO
— sitting exactly at the q6_0 point, confirming q5_0/q6_0 are quality-equivalent on 27B and the choice
between them is pure size, #531). Provenance: `.opencoti/tcq-survivors-27b.sh` + `.opencoti/s5b-rerun.sh` →
`.opencoti/ppl-kld/27b-survivors.tsv` (+ `.q5note`); DCA-on column from `.opencoti/s5b-dca-fidelity.sh`.

### 5b-8B. Scalar + asymmetric K/V — extended eval (8B instrument, historical)

Full matrix — **every cell ran; no unsupported combos** (the in-register FA-VEC path serves all the
mixed K/V pairs below). _Historical-collection note (superseded by #531):_ when these 8B numbers were
collected, the DSO was the minimal build (GPU FA-VEC instances for f16/q8_0/q4_0/bf16 only), so `q5_1`/`q5_0`
ran through a slow CPU-FA fallback (~107 s/pass). **The values stand unchanged** — CPU-FA and GPU FA-VEC
compute identical attention, so KLD/PPL are DSO-invariant (only wall-clock differed). On the **current shipped
all-quants DSO (#531) every scalar pair, `q5_1`/`q5_0` included, runs native GPU FA-VEC — nothing falls back
to CPU-FA** (re-confirmed on 27B in §5b above, where `q5_0` went GPU FA-VEC). f16 ref PPL: noDCA 9.451 · DCA 9.441.

| config | ctk/ctv | PPL noDCA | KLD noDCA | top% noDCA | PPL DCA | KLD DCA | top% DCA |
|--------|---------|-----------|-----------|------------|---------|---------|----------|
| q8_0     | q8_0/q8_0     | 9.447 | 0.00086 | 98.8 | 9.449 | 0.00135 | 98.3 |
| q5_1     | q5_1/q5_1     | 9.470 | 0.00605 | 96.9 | 9.603 | 0.0230  | 93.7 |
| q5_0     | q5_0/q5_0     | 9.485 | 0.00703 | 96.9 | 9.496 | 0.0183  | 94.3 |
| q4_0     | q4_0/q4_0     | 9.601 | 0.0329  | 92.6 | 9.664 | 0.0560  | 90.0 |
| **q8K/q4V**  | q8_0/q4_0   | 9.469 | **0.00282** | 97.8 | 9.491 | 0.00461 | 97.3 |
| **f16K/q4V** | f16/q4_0    | 9.440 | **0.00281** | 97.8 | 9.490 | 0.00432 | 97.3 |
| **t8K/t4V**  | turbo8/turbo4 | 9.510 | **0.00814** | 96.3 | 9.468 | 0.00767 | 96.3 |
| t4K/t2V  | turbo4/turbo2 | 10.47 | 0.172 | 82.9 | 10.13 | 0.140 | 84.3 |
| t3K/q4V  | turbo3/q4_0   | 12.78 | 0.426 | 75.3 | 10.19 | 0.183 | 82.6 |

**Reading.**
- **Scalars — DCA costs a *little*, the inverse of turbo.** The noDCA FA reads scalar KV faithfully,
  so it is the reference-quality path; DCA's f16-lift adds a small round-trip (q8 0.0009→0.0014,
  q4_0 0.033→0.056). Both fine (top 90–99%). Compare §5a, where the noDCA *turbo* in-register read is
  the lossy path so DCA *helps*. Rule of thumb: **scalar KV → noDCA is the quality path; turbo KV →
  the dequant-on-lift (DCA/#444) is the quality path.**
- **Asymmetric is the memory sweet spot.** **q8K/q4V** and **f16K/q4V** both land at **KLD ≈ 0.003,
  top ≈ 98%** — near-q8 quality at q4-sized V. K-precision dominates; raising K past q8 (→f16) buys
  nothing, V is the compressible side. **t8K/t4V** is the turbo analogue (**KLD ≈ 0.008**, top 96%):
  turbo8-K rescues turbo4-V — 17× better than symmetric turbo4 (0.14). These are the recommended
  long-context KV recipes.
- **The turbo2 degeneracy is K-side.** Symmetric turbo2 noDCA is catastrophic (KLD 5.60, §5a), but
  **t4K/t2V** — turbo2 on *V only*, turbo4 K — is fine (**KLD 0.172** noDCA). So the in-register 2-bit
  failure is the **K-read (`vec_dot_KQ`)**, not the V-read: turbo2 is usable on the V side or via the
  faithful lift, never as the in-register K type. (refines `.wolf/buglog.json` bug-583.)

### 5b-8B-ctx. KV-quant × DCA across the context ladder (#580, bs2 dual-Blackwell, 2026-07-01)

Extends the §5b-8B single-ctx (2048) matrix into a **ctx ladder 2k → 128k** on the same instrument
(Qwen3-8B-Q8_0, `TURBO_INNERQ_SCALE` head_dim 128). Ran on **bs2** (2× RTX PRO 6000 Blackwell, GPU0 =
2k/4k/8k/32k, GPU1 = 64k/128k) via the GPU-perplexity binary with DCA re-exposed to `--kl-divergence`.
Corpus `wiki.long` (test.mid+valid.mid, ~151k tok; 128k used a 2× concat, ~302k tok — perplexity needs
**2× ctx** tokens per window). Chunk = 1024 (2k/4k/8k), 2048 (8k variant), **8192** (32k/64k/128k =
production chunk). **Qwen3-8B native `n_ctx_train` = 40960**, so 64k = 1.6× and 128k = 3.2× native — the
only two cells where DCA actually engages; 2k–32k are sub-native (DCA ≈ no-op).

**(a) DCA rescues f16 coherence past native — the headline.** f16 reference PPL, no KV quant:

| ctx | ×native | f16 PPL noDCA | f16 PPL DCA |
|-----|---------|---------------|-------------|
| 2k   | 0.05× | 8.22  | 8.22 |
| 4k   | 0.10× | 8.29  | 8.32 |
| 8k   | 0.20× | 8.00  | 8.02 |
| 32k  | 0.80× | 7.70  | 7.77 |
| 64k  | 1.6×  | 8.28  | 8.39 |
| 128k | 3.2×  | **19.16** | **7.34** |

Plain attention survives to **1.6× native** (64k PPL 8.28, ~unchanged) but **breaks at 3.2×** (128k PPL
**19.16**); **DCA-on holds PPL at 7.34** — a clean, direct measurement of DCA extending usable context on
the f16 reference itself. (Below native, DCA costs a hair — expected, it's a no-op there.)

**(b) On the DCA path the KV-quant ladder is ctx-invariant — except 2–3-bit turbo.** KLD (DCA, vs each
regime's own f16 base):

| tier | ctk/ctv | 2k | 4k | 8k | 32k | 64k | 128k |
|------|---------|----|----|----|-----|-----|------|
| q8_0        | q8_0/q8_0     | 0.0014 | 0.0015 | 0.0012 | 0.0011 | 0.0012 | 0.0011 |
| turbo8      | turbo8/turbo8 | 0.0019 | 0.0017 | 0.0014 | 0.0013 | 0.0015 | 0.0013 |
| **f16K/q4V**| f16/q4_0      | 0.0041 | 0.0038 | 0.0033 | 0.0029 | 0.0031 | **0.0028** |
| **q8K/q4V** | q8_0/q4_0     | 0.0044 | 0.0046 | 0.0037 | 0.0033 | 0.0037 | 0.0032 |
| **t8K/t4V** | turbo8/turbo4 | 0.0077 | 0.0069 | 0.0063 | 0.0057 | 0.0061 | 0.0055 |
| q5_0        | q5_0/q5_0     | 0.0187 | 0.0187 | 0.0180 | 0.0165 | 0.0186 | 0.0161 |
| q4_0        | q4_0/q4_0     | 0.0558 | 0.0558 | 0.0563 | 0.0562 | 0.0627 | 0.0662 |
| turbo4      | turbo4/turbo4 | 0.0777 | 0.0711 | 0.0653 | 0.0592 | 0.0659 | 0.0626 |
| turbo3      | turbo3/turbo3 | 0.180  | 0.185  | 0.194  | **1.335** | 2.375 | 2.221 |
| turbo2      | turbo2/turbo2 | 0.636  | 0.675  | 0.733  | **2.893** | 3.111 | 3.911 |

(8k column = chunk-1024 variant; chunk-2048 is within noise except turbo2-DCA, where the coarser chunk is
worse — 1.22 vs 0.73 — so **smaller DCA chunks help the fragile low-bit tier**.)

**Reading.**
- **The §5b-8B recipe holds to 3.2× native.** q8_0/turbo8 (~0.001), q5_0 (~0.017), q4_0/turbo4 (~0.06),
  and the asymmetric hi-K/cheap-V winners **f16K/q4V · q8K/q4V · t8K/t4V (~0.003–0.008)** are **flat
  across the whole ladder** — the single-ctx conclusion (asymmetric hi-K/cheap-V = the long-ctx sweet
  spot) is now confirmed to extend, unchanged, to 128k.
- **2–3-bit turbo is a sub-native economy only.** turbo2/turbo3 are fine at ≤8k (turbo3-DCA 0.18–0.19)
  but **cross into unusable right around native** — turbo3 jumps to 1.34 @32k, 2.38 @64k; turbo2 to
  2.9 @32k. **turbo4 is the low-bit floor that survives** (0.06 through 128k, and DCA *lowers* it vs
  noDCA — the §5b turbo/lift rule). Serving past native ⇒ **≥4-bit KV with a high-precision K side**.
- **The DCA×quant sign split (§5b-8B) persists at every ctx:** DCA slightly *raises* scalar-quant KLD
  (q4_0 noDCA ~0.025 → DCA ~0.056) but *lowers* the turbo dequant-lift KLD (turbo4 ~0.087 → ~0.063).
- Provenance: `.opencoti/ppl-kld-4k8k.sh` + bs2 `bs2-driver.sh`; per-ctx matrices at bs2
  `/srv/ml/opencoti-c1/ppl/out/ppl-kld-<ctx>/matrix.md`. Corpus-size gotcha (perplexity needs 2× ctx
  tokens) = buglog bug-2093; the GPU-perplexity DCA re-exposure was a temporary `arg.cpp` edit (reverted).

### 5b-14B-1M-ctx. KV-quant × DCA ladder on the 1M-native production class (#581, bs2 GPU1, 2026-07-01→04)

Re-runs the §5b-8B-ctx ladder on **Qwen2.5-14B-Instruct-1M-Q8_0** — the HAL/1M serving vehicle
(`n_ctx_train` = 1M native, no YaRN) — ctx **2k → 256k**, 13 KV configs × {noDCA, DCA} per tier,
corpus `wiki.14b.raw`, chunk 1024 (2k/4k) / 2048 (8k) / 8192 (32k+). Driver
`bs2:/srv/ml/opencoti-c1/ppl/bs2-driver-14b.sh`; matrices `…/ppl/out14b/ppl-kld-<ctx>/matrix.md`.
Crucially, **every rung here is *sub-native*** for this model — so this ladder measures intrinsic
long-range quant sensitivity, not DCA rescue.

**(a) KLD (noDCA, vs same-regime f16 base) — the ladder.** 256k\* = partial (5–6/9 chunks; the
3600 s/cell cap timed out — f16 base alone needs 478 s/pass — cumulative KLD from the cell logs,
stable to 3 digits by chunk 5):

| tier | ctk/ctv | 2k | 4k | 8k | 32k | 128k | 256k\* |
|------|---------|----|----|----|-----|------|-------|
| q8_0 | q8_0/q8_0 | 0.0023 | 0.0023 | 0.0023 | 0.0024 | 0.0029 | 0.0051 |
| turbo8 | turbo8/turbo8 | 0.0034 | 0.0034 | 0.0034 | 0.0035 | 0.0040 | 0.0067 |
| **f16K/q4V** | f16/q4_0 | — | 0.0082 | 0.0081 | 0.0080 | 0.0087 | 0.0128 |
| **q8K/q4V** | q8_0/q4_0 | — | 0.0084 | 0.0083 | 0.0082 | 0.0089 | — |
| q5_1 | q5_1/q5_1 | 0.0124 | 0.0125 | 0.0126 | 0.0129 | 0.0142 | 0.0194 |
| q5_0 | q5_0/q5_0 | 0.0147 | 0.0148 | 0.0149 | 0.0153 | 0.0170 | 0.0250 |
| **t8K/t4V** | turbo8/turbo4 | — | 0.0198 | 0.0195 | 0.0191 | 0.0206 | 0.0326 |
| q4_0 | q4_0/q4_0 | 0.0525 | 0.0536 | 0.0546 | 0.0558 | 0.0623 | 0.0836 |
| turbo4 | turbo4/turbo4 | 0.115 | 0.118 | 0.122 | 0.131 | 0.154 | 0.232 |
| t4K/t2V | turbo4/turbo2 | — | 0.234 | 0.238 | 0.247 | 0.286 | 0.437 |
| t3K/q4V | turbo3/q4_0 | — | 0.235 | 0.243 | 0.272 | 0.319 | 0.466 |
| turbo3 | turbo3/turbo3 | 0.250 | 0.263 | 0.272 | 0.301 | 0.356 | 0.524 |
| turbo2 | turbo2/turbo2 | 1.30 | 1.42 | 1.51 | 1.72 | 2.13 | 2.89 |

(2k asym + all 2k-DCA and 64k-noDCA cells are **harness artifacts**, not quality data — truncated f16
base `.dat` → `kl_divergence: failed reading log-probs`; the 256k "FAIL" wall in `matrix.md` is the
per-cell timeout, not a crash. DCA columns at 4k–128k track noDCA with the usual §5b sign split;
@256k-DCA partials: q8_0 0.0065 · q5_1 0.0427 · q5_0 0.0866 · q4_0 0.296 · turbo2 3.19.)

**Reading.**
- **The frozen 14B is more quant-sensitive than the 8B — and degradation grows with ctx even
  sub-native.** Where 8B turbo3-DCA sat at 0.18–0.19 sub-native, 14B turbo3 starts at **0.25 @2k**
  and climbs to **0.52 @256k**; turbo2 is dead everywhere (1.3→2.9). Every low-bit tier roughly
  doubles from 2k→256k while q8/turbo8 stay ≤0.007 — long-range attention amplifies K/V error on
  this model; there is **no safe regime for 2–3-bit turbo here**, unlike the 8B.
- **The serving recipes hold to 256k:** q8_0/turbo8 (≤0.007), asym **f16K/q4V ≈ q8K/q4V
  (0.008–0.013)**, **t8K/t4V (0.02–0.03)**, q5-class ≤0.025; **turbo4 is again the low-bit floor**
  (0.23 @256k — usable, no margin).
- **DCA on a native-1M model costs, as expected** (Qwen2.5-1M needs no extension): f16 ref PPL @128k
  noDCA 3.486 vs DCA 3.886 — approximation cost; the DCA columns are composition coverage, not a
  recommendation for this model.
- **HAL (#582) implication — the last lever is now quantified.** Route (b) "low-bit history ⊕ exact
  recent" cannot use turbo2/3 history on this class (0.5–2.9); it needs **≥4-bit with a
  high-precision K side** (t8K/t4V 0.033, q8K/q4V ~0.01 @256k), capping the history-compression win
  at ~4× vs f16 rather than the 8–10× a 2–3-bit history would give. Route (a) host-stream-exact is
  unaffected.

### 5x. WS2 turbo-V in-register — the KV-decode-tps win (#629, DEFAULT-ON)

**WorkStream-2 = read a rotated turboN V-cache IN-REGISTER inside the multichunk DCA fused
flash-attn kernel**, killing the per-forward whole-cache `cpy_turboN_f16` cast (a context-growing
decode bottleneck — the same D512-global materialize tail that sank WS1's turbo-MMA @256k, §5a /
poly_kv.md S2). Gated by an `n_q≤16` gate: **in-register** for decode + small spec-verify batches;
**prefill keeps the byte-identical f16-lift path**. Now **DEFAULT-ON**.

**Losslessness gating (read this before the table).** This is a **vec-only** kernel change, so
**PPL/KLD are BLIND to it** (they run the MMA/prefill path — same blindness as sparse-V §10, decode
levers). The authoritative gates are **RULER niah** (retrieval) + **teacher-forced logit-equivalence**
(`real_frac` = fraction of tokens whose argmax moved, `mean_tv` = mean top-k total-variation,
`ffa` = full-faithful-argmax rate). Not PPL, not KLD.

**Full matrix — all @256k, ctk=q8_0, DCA-on chunk 32768.** "ref" = f16-lift (`WS2=0`), "ours" =
in-register (`WS2=1`); decode tps.

**D512 — Gemma (global head_dim 512, iSWA):**

| model · tier | ref tps | ours tps | Δ | real_frac | mean_tv | ffa | niah (n) |
|---|---|---|---|---|---|---|---|
| A4B turbo2_0   | 48.2 | **91.2** | **+89%** | (see A4B block below) | — | — | 100 |
| A4B turbo3_0   | 43.0 | **80.7** | **+88%** | 0.0 | 0.00113 | 1.0 | 100 (5) |
| A4B turbo2_tcq | 39.8 | **66.8** | **+68%** | 0.0 | 0.01784 | 1.0 | 100 (5) |
| A4B turbo3_tcq | 37.6 | **64.5** | **+72%** | 0.0 | 0.01078 | 1.0 | 100 (5) |
| 31B turbo2_0 (dense+SWA) | 11.7 | **21.6** | **+85%** | 1.0 ⚠ | 0.0137 | 0.0 ⚠ | **100** (5) |

**D256 — Qwen-arch (global head_dim 256; qwen35 / qwen35moe, no SWA, native 256k):**

| model · tier | ref tps | ours tps | Δ | real_frac | mean_tv | ffa | niah (n) |
|---|---|---|---|---|---|---|---|
| omni27 turbo3_0   | 15.0 | **27.9** | **+86%** | 0.0 | 0.00107 | 1.0 | 100 (5) |
| omni27 turbo2_tcq | 13.5 | **25.2** | **+87%** | 0.0 | 0.00735 | 1.0 | 100 (13) |
| omni27 turbo3_tcq | 12.6 | **24.6** | **+95%** | 0.0 | 0.00378 | 1.0 | 100 (13) |
| qw35a3 turbo3_0   | 43.0 | **76.1** | **+77%** | 0.0 | 0.00919 | 1.0 | 100 (5) |
| qw35a3 turbo2_tcq | 40.5 | **75.5** | **+86%** | 0.0 | 0.01644 | 1.0 | 100 (13) |
| qw35a3 turbo3_tcq | 39.1 | **75.0** | **+92%** | 0.0 | 0.01428 | 1.0 | 100 (13) |

turbo2_0 on D256 (omni27, qw35a3) is a **clean +86–98% win** too — see the eval-cell artifact caveat
below; the number 15.8/15.8 (omni27) and 49/49 (qw35a3) you may find in the `ws2-eval-cell.sh` output
are a **measurement artifact**, not zero benefit.

**Two caveats (documented honestly, not hidden):**

1. **31B turbo2_0 TV top-k-SET churn.** This one cell shows `real_frac 1.0 / ffa 0.0` yet `mean_tv`
   only **0.0137** — the distribution mass is ~identical but the top-20 **membership** reorders in the
   tail (a TV-metric artifact on the SWA model), **NOT** a correctness failure. **niah 100** (n=5) is
   the authoritative retrieval gate and it passes clean. Do not over-claim bit-losslessness for this
   cell; do read it as retrieval-lossless.
2. **D256 turbo2_0 eval-cell tps artifact.** The `ws2-eval-cell.sh` tps phase self-measured ours≈ref
   (omni27 15.8/15.8, qw35a3 49/49) — a **known boot mis-attribution** in that harness (both arms
   booted into the same env), NOT zero benefit. The clean per-boot-env A/B (`ws2-qwen-ab2.sh`) shows
   the real **+86–98%** wins, fully consistent with the turbo3_0 / *_tcq cells in the same rows.

**Perf-regression before/after (bug-2140 fatbin-last DSO is perf-free).** The pure `-Wl` fatbin-last
layout change carries **zero kernel-perf cost** — A4B turbo2_0 @256k:

| build | WS2 | decode tps | prefill tps |
|---|---|---|---|
| bug-2140 DSO | 0 | 48.22 | 4388 |
| baseline      | 0 | 48.1  | 4435 |
| bug-2140 DSO | 1 | 91.2  | 4406 |
| baseline      | 1 | 91.2  | 4433 |

All deltas ≤1% noise → the fatbin-last relayout is confirmed perf-free; the +89% is the WS2 kernel,
not a build artifact.

**Scalar-KV reference (cost-of-compression).** A4B & 31B D512 q8_0/q8_0 and q8_0/q4_0 scalar baselines
were captured (VRAM bits: q8=8, q4=4, turbo3=3, turbo2=2) — see the `ws2-scalar` cells in the eval
dir for the numbers.

**Ctx-ladder (A4B turbo2_0) — the win GROWS with context.** From the per-ctx tps sweep
(`ws2-s2-tps/results.tsv`, ref=`WS2=0` f16-lift, ours=`WS2=1` in-register, decode tps median of 3):

| ctx | ref tps | ours tps | Δ | prefill (ref/ours) |
|---|---|---|---|---|
| 128k | 73.3 | **113.6** | **+55%** | 6014 / 6076 |
| 256k | 48.1 | **91.2** | **+89%** | 4436 / 4433 |
| 512k | 28.5 | **57.3** | **+101%** | 2885 / 2871 |

This is the direct signature of the WS2 mechanism: the eliminated cost is the per-forward
whole-cache `cpy_turboN_f16` materialize cast, an **O(n_kv) cost that grows with context**, so
removing it wins *bigger* as ctx grows (+55 → +101% over 128k→512k) — the mirror image of WS1's
register-spill loss that grew *worse* with ctx. Prefill is at parity at every rung (the `n_q≤16`
gate keeps prefill on the byte-identical f16-lift path).

**Default-on policy.** WS2 in-register turbo-V is **DEFAULT-ON** — it is a serving-path decode win
(+68–95% @256k across both arches and every turbo/TCQ tier), retrieval-lossless (niah 100 everywhere)
and logit-lossless everywhere except the one SWA top-k-churn caveat. It composes with the MTP draft
path (see [mtp.md §3g](mtp.md) — both lossless, both stack) and is the opposite verdict of WS1's
turbo-MMA null (§5a / poly_kv.md S2): WS1 was noDCA and the D512 cast it had to beat was still paid;
WS2 is DCA-on multichunk-fused and eliminates that cast in-register. Cross-refs:
[three-way-tps.md](three-way-tps.md) (3-way tps harness + model registry),
[poly_kv.md S2](../features/poly_kv.md) (WS1↔WS2 contrast).

### 5c. Status / optional follow-ups
- **§5b-14B-1M-ctx (#581) — DONE 2026-07-04** (above): ladder 2k→256k on the 1M-native 14B; recipes
  hold, 2–3-bit turbo has no safe regime on this class, HAL route-(b) floor = 4-bit hi-K.
- **HAL #582 — DECIDED 2026-07-05**, full study in
  [hal_kv_compression.md](hal_kv_compression.md): resident compression (q8K/q4V default) wins;
  host-stream-exact is 22–27× slower at equal ctx (0.99 tps @64k on 50 GB/s PCIe) → overflow
  fallback only; quant decode on the 14B is kernel-bound not bandwidth-bound (q4/q4 == q8K/q4V
  tps; ~2× vs f16, ~6× below bandwidth ceiling) → P0 kernel work; native-1M fits one 96 GB card
  only compressed (192 GiB f16 → 78 GiB q8K/q4V).
- **Scalar/asym cells — LOCKED** (§5b full matrix) **and ctx-swept 2k→128k (§5b-8B-ctx, #580, DONE
  2026-07-01):** the asymmetric hi-K/cheap-V recipes stay flat (~0.003–0.008) to 3.2× native; DCA
  rescues f16 PPL at 128k (19.2→7.3); 2–3-bit turbo collapses past native, turbo4 is the low-bit floor.
- **TCQ tiers (#447)** `turbo2_tcq`/`turbo3_tcq` — **DONE + target-class verified** (§5a-TCQ-27B:
  Qwen3.6-27B turbo3_tcq KLD 0.037, turbo2_tcq 0.071, both beating their plain siblings). The 8B/1.5B
  in-register low-bit collapse is **model fragility, not a kernel defect**; TCQ ships as-is on
  27B-class/Gemma-4 targets, f16-lift reclassified to optional small-model support.
- **Gemma-4 head_dim-512 (1M production target)** — **DONE**: PPL/KLD pointed at Gemma-4-A4B found the
  instrument **invalid** on the omnimerge GGUFs (§5a-TCQ-A4B-KLD / bug-631), so quality-in-use is validated
  via RULER niah (§5a-TCQ-RULER) + the §5b cross-instrument matrix instead.
- Provenance: runner `.opencoti/ppl-kld-matrix.sh`; per-cell logs `.opencoti/ppl-kld/*.log`; matrix
  `.opencoti/ppl-kld/matrix.{tsv,md}`; GPU-perplexity link `.opencoti/ppl-link.mk` + `ppl_main_gpu.cpp`.

---

## 6. Campaign status & open items

Both eval campaigns are **complete**; no GPU jobs are running.

- **TCQ codebook campaign (#523–525, solidpc):** concluded — final verdict in §5a-TCQ-CB (the deployed
  `turbo3_tcq` symmetric + the #513 asym are already at the TCQ frontier; none of {codebook retrain,
  free state-widen, wide-K `_w`-asym} beats them; the buggy/redundant `_w` tier was reverted in #527).
- **bs2 long-context quality ladder:** finished; bs2 GPUs idle of ladder work.

| GPU | arm | final state | last cell |
|-----|-----|-------------|-----------|
| bs2 GPU0 | RULER-VT | **complete** — 256k/512k/768k/1M all landed (0.976·0.960 / 0.984 / 0.956 / **0.876**, §1a; 1M corrected 07-01 from server-crash 0.716) | `ruler_native_vt_1024k_dcaon` ended 2026-06-15; 1M 9-sample re-fix 2026-07-01 |
| bs2 GPU1 | MRCR | **complete** — n=50 `mrcr_256k_dcaoff/on` + `512k` (0.1138 / 0.1320 / 0.1027); 768k_synth/1M small-n (0.1259 / **0.0273**); + quant-KV cell `q8_c1` @256k-on **0.0999** (< f16-off; §1b) | `mrcr_256k_dcaon_q8_c1` landed 06-24 |

Driver: `bs2:/srv/ml/omk_mrcr_dca/dca_quality_ab_bs2.sh` (logs `bs2:/srv/ml/omk_mrcr_dca/ladder_logs/`).
**RESOLVED (2026-07-01):** the 9/50 empty completions at 1M (§1a) were a **serving artifact** —
`ConnectionError` after the F16 server crashed at sample 40, not coherence loss. Re-running just the 9 on a
fresh server (cache-resume) gives the true n=50 VT-1M = **0.876**; the 0.716 is retired.

> **Metric-field caveat (read scores from `scores.metric`).** `summary.json`'s *top-level* `metric`
> field is a generic roll-up label that prints `pass_at_1` for MRCR — it is **not** the real metric.
> The authoritative metric is `scores.metric` = `sequence_matcher_ratio` (MRCR) / `string_match_all`
> (RULER-VT). All scores in §1 are the canonical `summary.json` `.score`.

---

## 7. Provenance / source paths

- **Quality scores (canonical):** `bs2:/srv/ml/omk_mrcr_dca/results/<template>/<served>/summary.json` `.score`
- **Per-cell server logs (tps, KV/VRAM):** `bs2:/srv/ml/omk_mrcr_dca/results/<template>/<served>/server.log`
- **Templates:** `bs2:/srv/ml/omk_mrcr_dca/omnimergekit/eval/templates/{ruler_native_vt,mrcr}_*_dcaon.yaml`
- **3-arm gen-tps:** `solidpc:backup_models/scripts/dca_gentps_3arm/` (`run.log`, `resp_dca{on,off}.json`)
- **Coherence/regression gates:** `solidpc:backup_models/scripts/dca_gate623_mc_coherence.sh`, `dca_gate_gemma_mc_regress.sh`
- **NIAH ladder:** `solidpc:backup_models/scripts/dca_niah_ladder_618.sh` → `bs2:/srv/ml/dca/dca_niah_ladder_618/`
- **Patch + RCA:** `vendors/patches/llamafile/0078-dca.patch`; `backup_models/.wolf/{buglog.json,cerebrum.md,memory.md}`
- **DSO under test:** solidpc `df4c46bca8a4b092` (build #4, qwen fix); bs2 `30ed439580de858c` (Gemma-validated; byte-identical on the Gemma DKQ=512 path by construction).

## 8. MTP × DCA composition at 256k (#431/#439)

_bs2 GPU1, 2026-06-29/30._ Speculative MTP (both engines) composes logit-equivalently with
**inter-chunk DCA at 256k** — the decisive long-context composition cell (full detail in
[`mtp.md`](mtp.md) §4c/§5):

> **⚠ The Gemma (#431) row was bug-2118-contaminated — RE-CONFIRMED on the fixed binary (2026-07-10).**
> When this cell was first logged, bug-2118 made `--dca on` a silent no-op on Gemma, so its
> `real_frac=0` measured DCA-**off**. Re-run with **genuine** DCA on the shipped WS2 binary
> (`6468ae37`/`cb8f942d`): **`real_frac=0.0`, `frac_full_agree=1.0` → still PASS** (§12 Tranche 4c).
> The Qwen NextN (#439) row is a full-attention path and was never bug-2118-affected.

| engine | model | recipe | verdict |
|---|---|---|---|
| Qwen **NextN** self-spec | Qwen3.6-27B-Omnimerge Q6_K | `-c 262144 --dca on --dca-chunk-size 32768` (8 chunks), ref=plain / cand=`--spec-type draft-mtp` both DCA-on | **PASS** `real_frac=0` (#439) |
| Gemma **assistant-MTP** | Gemma-4 A4B-it Q6_K + adapted `gemma4-assistant` drafter | same recipe, cand=`--spec-type draft-assistant -ngld 99` | **PASS** `real_frac=0` (#431) |

So MTP verify is bit-equivalent to plain decode over DCA-laid-out KV at 256k (the `mean_tv_advisory`
non-zero is the known empty-top-logprobs artifact for spec-accepted tokens; `real_frac` is the gate).
Separately, rolling-KV **POSITION_WINDOW × MTP** stands on logit-equivalence only — its 256k *engagement*
is architecturally N/A on the current binary (Gemma iSWA window-mode ineligibility, bug-797;
[`mtp.md`](mtp.md) §5).

## 9. All-KV-types DCA breadth matrix + q6_0 fix (#444–447)

_2026-06-24, bs2 GPU0._ Goal: prove DCA works with **every** K/V type and asymmetric combo, not just the
per-type C-series logit-equiv gates. Harness `.opencoti/dca/dca-allkv-matrix.sh` (Qwen3.6-35B-A3B-redl,
IQ3_XXS, 128 head_dim; DCA-on `--dca-chunk-size 512` so cross-chunk attention engages; count-up coherence,
longest monotone +1 run, FLOOR 250 / 1500 n_predict). Control `dca-allkv-control.sh` re-runs the
non-passing cells DCA-**off** to separate DCA-path bugs from intrinsic tier quality.

**Matrix verdict (26 combos):** 18/26 COHERENT. Findings:

| class | combos | verdict |
|---|---|---|
| scalar sym | f16, bf16, q8_0, q5_1, q5_0, q4_0 | ✓ COHERENT |
| scalar asym | q8_0/q5_1, q5_0/q4_0, f16/q4_0, bf16/q8_0 | ✓ COHERENT |
| turbo | turbo3, turbo4, turbo8, turbo3_tcq (sym); turbo3/turbo2, q8_0/turbo3 (asym) | ✓ COHERENT |
| **q6_0 (any position)** | q6_0/q6_0, q8_0/q6_0, q6_0/q4_0 | **🔴 CRASH → FIXED** |
| 2-bit / marginal | turbo2, turbo2_tcq (sym); turbo3/q8_0, turbo3_tcq/turbo2_tcq (asym) | ⚠ intrinsic quality, **not DCA** |

**q6_0 was the only real DCA defect** (bug-694). `dca_lift_to_f16()` in `dca.cpp` had a `scalar_quant`
whitelist missing q6_0 (added later, #512), so q6_0 took a direct `ggml_cast(q6_0→f16)` with no CUDA cpy
kernel → CPU `dup_from_q` abort at `ggml-cpu/ops.cpp:594`. **Fix:** add `GGML_TYPE_Q6_0` to the whitelist
(lifts q6_0→f32→f16 on GPU like q5_0). Host-only rebuild (`c081ea54`→`7c1d4ca8`, DSO untouched), captured into
`0081` (re-capture proven byte-identical). **Re-test on bs2 gpu0:** all 5 q6_0 DCA-on combos COHERENT 318
(q6_0/q6_0, q8_0/q6_0, q6_0/q4_0, f16/q6_0, q6_0/f16).

**The ⚠ collapses are NOT DCA bugs** — the DCA-off control proves it: turbo2 (84 off / 140 on), turbo2_tcq
(113 / 68), turbo3/q8_0 (188 / 159) all collapse *equally or worse* with DCA off → intrinsic 2-bit-tier /
marginal-mix lossiness on the count-up task. turbo3_tcq/turbo2_tcq is the one DCA-sensitive case (318 off →
173 on) — a weak 2-bit V pushed over by DCA's harder positional task, a quality limit not a correctness bug.

**Net:** DCA is correct across the full scalar ladder (f16/bf16/q8_0/q6_0/q5_1/q5_0/q4_0) + turbo3/4/8 +
turbo3_tcq, symmetric and asymmetric. The only non-passing cells are 2-bit tiers at their intrinsic quality
floor. C-series "DCA all-KV" (#444–447) is empirically complete on a real model.

## 10. Sparse-V — attention-gated V-skip (#546/#549/#552/#565/#566/#567)

Decode-time optimization: skip the V-contribution of low-attention keys (quantized-V only; f16/bf16 V is a
no-op by kernel construction). Two threshold knobs: a **static** `TURBO_SPARSE_V_TAU` (skip keys whose
softmax weight < τ) and an **adaptive** mass-budget `TURBO_SPARSE_V_EPS` (#565, skip while total dropped
softmax mass < ε). **Headline verdict:** the win is **iSWA-static-τ=0.05** (concentrated global V-cache →
a fat skippable low-weight band); it is shipped self-configuring in the binary (#567 auto-policy, §10e). On
**full attention** the picture splits by model class (§10c): a static τ is a quality *cliff* on native-1M
diffuse-attention models, but a large lossless win on 256k-class merges; adaptive ε is always lossless but
yields no full-attn speedup (§10d).

### 10a. Directional probe — Qwen2.5-14B-1M @24k (3090, 2026-06-28) — not a verdict

Block-skip held at 50% coverage (proven lossless); swept `TURBO_SPARSE_V_TAU`. RULER niah_single_1,
12 samples, fixed seed 42. tps = max-over-niah-eval-lines (UNRELIABLE).

| cell | τ | niah | tps* |
|------|------|-------|------|
| dense | — | 100 | 17.97 |
| block-only | — | 100 | 21.50 |
| +V τ=0.1 | 0.1 | 0 | 24.96 |
| +V τ=0.05 | 0.05 | 91.67 | 25.35 |
| +V τ=0.02 | 0.02 | 75.0 | 33.23 |
| +V τ=0.01 | 0.01 | 91.67 | 36.55 |

*tps non-monotonic (rises as τ falls) → max-over-bursts metric is noise, not skip-tracking. No clean
lossless static τ on q8/14B-1M @24k (best niah 91.67): at 24k uniform per-position weight ≈ 4e-5, so the
whole 0.01–0.1 τ range sits above the thin-weight bulk and skips nearly all of it (all ≈ equally
aggressive, all lossy). Motivates adaptive τ (#565). KEEPER: block-skip alone = lossless q8 win
(niah=100, ~1.20× within-boot). Authoritative determination deferred to bs2 production models (§10b/c).

### 10b. Production iSWA validation — the lossless win (#566, bs2, 2026-06-29)

Binary C-series 511d5305 / 671f6f15, `-ctk q8_0 -ctv q8_0` (or `-ctv q8_0` over Q6_K weights).
niah_single_1 base seed 42; tps = MEDIAN per-sample decode at true ctx depth. Three production iSWA models,
all **niah 100 at every τ**:

**Gemma-4-A4B-62e Q6_K** — static τ is a lossless *decaying* win:

| ctx | dense tps | τ=0.05 (niah/tps/Δ) | τ=0.10 (niah/tps/Δ) |
|------|-----------|--------------------------|--------------------------|
| 64k | 112.97 | 100 / 124.56 / +10.3% | 100 / 124.76 / +10.4% |
| 128k | 91.10 | 100 / 97.85 / +7.4% | **96** / 96.61 / +6.0% |
| 256k | 64.08 | 100 / 67.18 / +4.8% | 100 / 67.94 / +6.0% |

**Official Gemma-4-31B-it Q6_K** (not a merge) — confirms the win at production scale:

| ctx | dense tps | τ=0.05 (niah/tps/Δ) | τ=0.10 (niah/tps/Δ) |
|------|-----------|------------------------|------------------------|
| 64k | 32.47 | 100 / 33.34 / +2.7% | 100 / 33.71 / +3.8% |
| 128k | 25.41 | 100 / 25.79 / +1.5% | 100 / 25.74 / +1.3% |
| 256k | 17.57 | 100 / 17.80 / +1.3% | 100 / 18.12 / +3.1% |

**Gemma-4-A4B-98e-v7-coder IQ4_XS** (the iSWA PRIMARY target) — lossless but FLAT on this 3090 vehicle:

| ctx | KV | V-skip | niah | decode tps | vs dense |
|------|-------|----------|-------|-----------|----------|
| 128k | f16 | off | 100 | 62.37 | — |
| 128k | f16 | τ=0.05 | 100 | 61.97 | -0.6% |
| 128k | f16 | τ=0.10 | 100 | 62.42 | +0.1% |
| 256k | q8_0 | off | 100 | 25.39 | — |
| 256k | q8_0 | τ=0.05 | 100 | 25.61 | +0.9% |
| 256k | f16 | off | 100 | 75.85 | — (probe at ~60k depth) |
| 256k | f16 | τ=0.05 | 100 | 75.59 | -0.3% |
| 256k | f16 | τ=0.10 | 100 | 75.41 | -0.6% |

VERDICT (iSWA): **static τ=0.05 is the safe always-on lossless setting.** On the bigger weight-bound
models (A4B-62e +5–10%, 31B +1–4%) it is a real decode win that *decays* with ctx (global V-cache fills →
smaller relative skip); the win is gentler on heavier per-token compute (31B < A4B-62e). On the f16-V
v7-coder the skip is a no-op (f16 V un-skipped by construction) so it is lossless-but-flat — composes
safely, no regression. The lone quality nick is A4B-62e 128k τ=0.10 (niah 96) → **τ=0.05 is the production
knob.** (v7-coder probe caveat: the fixed ~60k-token prompt measures decode at ~60k KV depth, not 256k;
niah is at true 256k.)

### 10c. Full-attention behaviour — static-τ cliff vs 256k-class lossless (#566, bs2, 2026-06-29/30)

Full attention splits by model class. **Native-1M Qwen2.5-14B-1M Q8_0** — static τ is a quality CLIFF:

| ctx | dense | τ=0.05 (niah/tps) | τ=0.10 (niah/tps) |
|------|-------|---------------------|--------------------|
| 64k | 28.45 | **60** / 41.46 (+46%) | **0** / 41.56 (+46%) |
| 128k | 18.26 | **8** / 27.52 (+51%) | **0** / 28.0 (+53%) |
| 256k | 10.01 | **0** / 18.85 (+88%) | **0** / 16.19 (+62%) |

**256k-class Qwen3.6-27B-Omnimerge-v4 Q6_K** (a sub-1M-native merge) — lossless AND large win:

| ctx | dense tps | τ=0.05 (niah/tps/Δ) | τ=0.10 (niah/tps/Δ) |
|------|-----------|-------------------------|-------------------------|
| 64k | 37.48 | 100 / 45.03 / +20% | 100 / 45.01 / +20% |
| 128k | 28.17 | 100 / 37.68 / +34% | 100 / 37.56 / +33% |
| 256k | 18.08 | 100 / 26.62 / +47% | 100 / 26.54 / +47% |

VERDICT: the static-τ cliff is a property of **native-1M diffuse-attention models specifically**, NOT of
full attention in general (a sharper finding than "no fixed τ is lossless on full attention"). The 14B-1M
is trained diffuse to the extreme → flat long-ctx weights → the skippable low-weight band *includes* the
needle's contribution, so any τ drops it (and harvests a big +46–88% speed in the process). The omnimerge
is a 256k-class merge with sharper long-ctx peaks → the needle's V stays above the τ floor while the
diffuse filler below it is safely skipped → +20–47% lossless. **Serving rule:** 1M-native full-attn → use
adaptive ε (#565, lossless-but-flat, §10d); 256k-class full-attn → static τ=0.05–0.10 is a real lossless
win. (14B-1M 128k-τ0.10 + the full 256k row filled 2026-06-30 from `sparse-v-566/qwen14b1m.tsv`.)

### 10d. Adaptive-τ mass-budget (#565) — lossless but no full-attn speedup (3090)

`TURBO_SPARSE_V_EPS`: skip key k iff its normalized contribution < ε/n_kv for every query column ⇒ total
dropped softmax mass < ε by construction (ε=0 ≡ byte-identical static). Two kernel defects were found and
fixed in `fattn-vec.cuh` (DSO `4326ca7807fe`, both paths byte-identical; knobs=0 ⇒ dense output-identical):
(1) **partial-L inversion** — old threshold divided the PARTIAL running softmax-denominator by the TOTAL
n_kv, so the per-key bar was too low and skip VANISHED as ctx grew; FIX = divide by keys-actually-processed
(true running mean); (2) **sink cliff** — added `TURBO_SPARSE_V_SINK` / `_RECENT` always-keep guards
(protect attention-sink + recent window incl. MTP draft tokens; run sink=64 recent=256).

Qwen2.5-14B-1M full attention, q8_0 KV, RULER niah_single_1, MEDIAN decode tps:

| ctx | dense | ε0.05+g | ε0.1+g | ε0.2+g | quality |
|-------|-------|---------|--------|--------|---------|
| 24576 | 14.36 | 14.02 | 13.28 | 13.65 | all niah 100 |
| 49152 | 9.25 | 9.12 | 9.16 | 9.22 | all niah 100 |
| 65536 | 7.56 | 7.29 | 7.29 | 7.36 | all niah 100 |

(64k single-ctx control: dense 7.83, static τ=0.05 → niah **33** / 11.91 (+52%, cliff repro); ε0.005–0.10 all
niah 100 / ~7.8–7.9 = flat.) FINDING: the combined fix DECISIVELY solves QUALITY (niah 100 in every cell,
cliff gone, inversion gone) but full attention yields NO decode win at any ε up to 64k (every cell
0.95–1.00× dense, flat across the whole ε range). ROOT CAUSE: a mean-relative threshold can only skip keys
BELOW the running mean; diffuse full-attention weights concentrate NEAR the mean, so the skippable
population is tiny regardless of ε — there is no fat sub-mean band to harvest. This is WHY the founding #546
"scales with ctx / more on full attn" assumption inverted: the win needs CONCENTRATED attention (iSWA's
small global V-cache), which full attention by construction lacks. NET: adaptive ε is the SAFE
full-attention default (never slower within noise, never lossy) but not a win there; the iSWA static-τ=0.05
win stands (§10b). Full-attention long-ctx speed is a different-mechanism problem (§11), not a V-skip
threshold problem.

### 10e. In-binary auto-policy (#567, patch 0088, host-only, 2026-06-29)

The §10b sparse-V win is now self-configuring so a STANDALONE `llamafile --server` gets it with no flags
(intelligence in the binary, NOT the opencoti TS adapter — a standalone CLI user bypasses the adapter). At
`llama_context` construction: if the user has not set `TURBO_SPARSE_V_TAU` AND the model is iSWA
(`hparams.swa_type != NONE`) AND V is quantized (`type_v` not f16/bf16/f32), `setenv(TURBO_SPARSE_V_TAU=0.05,
overwrite=0)`. The kernel reads that env (ggml-cuda is a runtime DSO → env is the cross-DSO channel) →
host-only, DSO byte-unchanged. Full-attention models leave it unset → dense byte-identical. Announced once
at WARN (model-load INFO is suppressed). GATE (3090, binary `5bf9fac6`): decision table 4/4 PASS — A4B q8_0
auto=ENGAGED; A4B q8_0 +`TURBO_SPARSE_V_TAU=0` override=off; A4B `-ctv f16`=off (kernel guard inert);
Qwen-14B-1M q8_0 full-attn=off (no iSWA). A/B @ 24k (A4B iSWA q8_0, 24 samples): dense niah 100 / 65.48 tps
vs auto niah 100 / 65.30 tps → LOSSLESS + non-slower (the iSWA win is tiny at 24k, grows with ctx — the
50-sample production runs in §10b carry the measurable win). The ε/sink/recent knobs remain available as
explicit overrides for full-attention experiments (no auto-default there — no lossless win).

### 10f. MTP composition (#549/#552) — parallel, turbo3_tcq, Qwen-NextN

Sparse-V composes with speculative MTP across all tested KV tiers and engines; the old "disable sparse-V
under MTP (kills draft acceptance)" guard is RETIRED (a pre-combined-kernel artifact).

**A4B iSWA q8_0 × assistant-MTP at `--parallel` ≥2** (3090, DSO `4326ca78`, draft acceptance = server-log
real_frac). Single-prompt per-slot: p1_off 0.805/114tps, p1_sv(τ0.05) 0.770/110.7; p2_off 0.832+0.796 /
52.6+51.8tps, p2_sv 0.847+0.837 / 53.3+52.8, p2_svguard(sink64 recent256) 0.847+0.819 / 54.3+54.6. All 6
per-slot samples in a 0.80–0.85 band (noise); sparse-V tps if anything slightly HIGHER. Multi-prompt (4
diverse coding prompts, parallel 2, mean accept): off 0.787, sv 0.819, svguard 0.819 → sv/svguard ≥ off,
per-prompt variance 0.74–0.89 dwarfs any sparse-V effect. (Harness gotchas, both in buglog: Gemma
assistant-MTP at `--parallel`>1 hard-requires `--kv-unified`; `wait $curlpid` only, not bare `wait`.)

**The two untested cells (#552, closed)** — combined kernel × MTP, greedy chat, single-stream, 3090.
CELL A (turbo3_tcq KV tier): A4B-v6 iSWA `-ctk/-ctv turbo3_tcq` + 26B-assistant MTP — A_off 0.7587 vs
A_sv (auto-engaged: WARN confirms "iSWA + quantized V (turbo3_tcq) → 0.05") 0.7587 = BYTE-IDENTICAL
acceptance; turbo3_tcq booted clean (no bug-631 garbage, 0.76 ≈ q8_0's 0.79). CELL B (Qwen NextN engine):
Qwen3.5-9B `--spec-type draft-mtp` q8_0 — B_off 0.6287 vs B_svF (`TURBO_SPARSE_V_TAU=0.05` FORCED; auto
leaves full-attn OFF) 0.6287 = BYTE-IDENTICAL (at 8k the full-attn skip is near-inert, but no mechanical
breakage of the NextN verify path). VERDICT: sparse-V composes with MTP across all KV tiers/engines —
q8_0×assistant (#549), turbo3_tcq×assistant (A), Qwen-NextN-self-spec (B). Byte-identical acceptance =
lossless-at-greedy. Production: auto-policy enables sparse-V only on iSWA+quant-V (incl. turbo3_tcq),
correctly OFF on Qwen full-attn — MTP and sparse-V are orthogonal there.

## 11. Sparse attention — block-selector / vertical-slash (#551, CLOSED) + #548 scout

The open problem this line chased: lossless-AND-faster decode at 256k/1M on **full-attention** models
(where §10 sparse-V has no win). Verdict (2026-06-29): the block-selector / vertical-slash line is **DEAD**
across all five mechanisms tried. The shipped long-ctx win remains §10 sparse-V on iSWA.

### 11a. Quest block-skip @256k — fails the win bar (bs2, 2026-06-29, PIVOTAL NEGATIVE)

Front A validated the proven 24k Quest block-skip win at real serving ctx (Qwen2.5-14B-1M Q8_0, q8_0 KV,
RULER niah_single_1 @262144, bs2 GPU1, binary 671f6f15 + sm120 DSO):

| cell @256k | niah | decode tps | note |
|------------|------|-----------|------|
| dense | 100.0 | 13.43 | baseline, n=4 |
| quest_65 | 75.0 | 13.04 | topk 2662/4096, recent 2048, sink 1 → LOSSY + NO win |

The 24k bug-747 result (q8 niah 100 lossless @65%, 1.34×@50%) does NOT extrapolate to 256k: (1) niah
collapses 100→75 at the SAME 65% coverage — Quest's geometric min/max kbounds score is an extreme-value
statistic, so as n_block grows 24k→256k (384→4096 blocks) the needle's lone constant-signal key is buried
by high-spread distractor blocks (SNR ~ 1/n_block); (2) no decode win (13.04 < 13.43, ~3% slower) — at 256k
the per-step selector overhead (kbounds fill + top-k over 4096 blocks EVERY decode step) cancels the
block-skip KV-read savings even though decode IS KV-bandwidth-bound there. Quest is a 24k-LOCAL win, fails
"must be a win even at 256k" on both axes.

### 11b. Decode-probe correction + bug-761 refresh trap

The flat ~13 tps above was a per-step SELECT-KERNEL artifact, not a property of block-skip. Decode-tps
probe (same model, ~231k prompt, 256-tok decode, bs2 GPU1): dense 14.05 (1.00×); q65_r1 (refresh 1,
per-step select) 12.84 (0.91× — select tax > skip saving); q65_r256 (refresh 256, amortized select) 26.87
(**1.91×**). So block-skip at ~50–65% coverage nearly DOUBLES 256k decode throughput once the
kbounds-fill+top-k-select over 4096 blocks is amortized off the per-step path — the speed half of the bar
IS clearable. BUT bug-761: `--sparse-attn-refresh 256` freezes the *first* decode token's pick (which
usually doesn't attend the needle) → **niah 0**. Mechanism (code read): Quest (mode 0) selects at
DECODE-time per token; `refresh N` trades correctness for speed. The correct per-step config (q65_r1) is
12.84 < dense → Quest cannot be both fast and lossless at 256k. The remaining gap is SELECTION QUALITY:
refresh changes WHEN select runs, not WHAT it picks.

### 11c. Line closed — five mechanisms exhausted + #548 scout-negative

The revival thesis (vslash content-selection with a wider question-window would find the needle where
Quest's geometric kbounds fails) was REFUTED on retest: restored `q_win` 8→64 (llama-graph.cpp:2871+3250),
host-rebuilt (sha `32460c35`), bs2 → vslash@24k f16 niah STILL 0 (zero movement). `q_win` is not the lever;
the real wall (buglog #563) is that the prefill question-window is a WORSE needle probe than the decode
answer-query (the decode query *generates* the needle; the prefill question doesn't reliably rank the
needle block) + recent-blocks frozen at prefill. A free MMA side-output would make prefill *scoring* free
but inherits the bad prefill-probe ranking → cannot fix selection correctness. **Five mechanisms now dead**
(Quest-geometric / max-logit / softmax-decode-q1 / prefill-window / q_win-restored); the only ever-lossless
variant (softmax-decode q_win=1) is 2.3× SLOWER + bimodal@40k. No lossless-AND-faster block-selector
exists. Tasks #568–572 (S2–S5 side-output) SHELVED.

**#548 importance-tiered bits SCOUT** (theTom turboquant_plus `layer-aware-v-compression.md`): LA-V7 =
V-only layer-aware (boundary L0,1,N-2,N-1 → q8_0-V; middle → turbo2-V; K=q8_0 all layers). theTom's OWN
numbers: advantage over uniform turbo2-V ≈ ZERO by 16k (-0.006 PPL @16k phi-4), "no speed penalty" → NOT a
256k win; dilutes with context, same per-token needle-ranking wall. theTom's central finding "ALL quality
loss is from K, not V" implies the only win-shaped salvage is layer-aware on K (unexplored bet) — DEFERRED
by user choice. **OPEN gap:** lossless+faster 256k decode on full-attention 1M-native models has no proven
lever; sparse-attention exploration is CLOSED.

## 12. #626 redo — Gemma×DCA evals on the FIXED binary (post bug-2118/2119/2120/2121)

**Why (2026-07-06):** bug-2118 made `--dca on` a silent no-op on ALL Gemma-4 archs, so every
historical Gemma×DCA number in this file (and mtp.md §#431/#441, the June MRCR A4B on/off pair,
the 256k/512k 3-model anchors) actually measured DCA-OFF. Fixing 2118 surfaced two criticals:
bug-2120 (dual-ctx drafter accept=0 with any quant target KV — attention-rotation not inherited
by the shared draft cache) and bug-2121 (deep-spill streaming-FA prefill corruption — CUDA-pool
staging scratch aliased across streams). All four are fixed and gated; patches 0099–0102.
Binary = llamafile.dualctx sha 91a017c8, DSO sha 8b23afbf. Historical Gemma×DCA rows above are
STALE for DCA-on claims; this chapter is the authoritative replacement as cells complete.

### Tranche 1 — 256k 3-model anchors (bs2 GPU0, 2026-07-06, first VALID Gemma DCA+MTP anchors)

212,327-token prompt, ctx 262144, q8_0-K/q4_0-V, window residency (all fully resident), greedy
needle + tps probe (`bs2-3model-anchors.sh`). Gemma cells run `--dca on --dca-chunk-size 32768`
+ dual-ctx assistant drafter; Qwen cell is native NextN (no DCA).

| cell | prefill t/s | decode t/s | draft accept | needle |
|---|---|---|---|---|
| A4B Q4_K_M + assistant-Q8_0, DCA on | 5200.2 | 73.5 | **0.700** (42/60) | PRESENT |
| 31B Q6_K + assistant-Q8_0, DCA on | 1148.9 | 26.9 | 0.456 (36/79) | PRESENT |
| Qwen3.6-35B UD-Q6_K NextN (native, no DCA) | 2811.8 | 109.7 | 0.606 (40/66) | PRESENT |

> **Decode-tps re-run — 2026-07-12, patch 0119 (P0 DCA-on scalar in-register), bs2 gate binary
> `7abd6840`.** The 2026-07-06 decode column above used the pre-0119 whole-cache `to_fp16_nc`
> f16-lift and is **stale-LOW**; on the current in-register DCA-on decode path the same cells
> (warmup + 256-tok cache-reused measure, all needle=PRESENT) are: **A4B 73.5→114.75 (+56%)**,
> **31B 26.9→33.34 (+24%)**, **Qwen-35B NextN 109.7→151.53 (+38%)**. Accept/needle unchanged
> (lossless — those columns stand). The Qwen measured call reports `prompt_n=516` (a self-spec
> draft-mtp cache-reeval quirk); needle=PRESENT confirms the full 256k context is resident.

Reading: the previously-impossible composition (Gemma + DCA-actually-on + quant KV + dual-ctx
drafter) now works end-to-end at 256k — accept 0.700 on A4B where the pre-fix binary scored
0.000 (bug-2120) on a config whose DCA flag did nothing (bug-2118). 31B accept 0.456 matches
its historically weaker adapted drafter, not a defect. 512k anchors + §5b niah matrix Gemma
cells + MRCR A4B on/off queued next.

**Losslessness gate (bug-2120 fix, 2026-07-06, bs2 A4B + assistant, 4k, n_max=1):** f16 —
plain vs dual-ctx spec token-IDENTICAL (40/40), spec deterministic. k8_v4 — spec deterministic
(specA==specB 40/40), accept 0.90, plain-vs-spec diverges at token 32: benign quant-KV
batch-vs-sequential greedy numerics (same class as the bug-858 upstream profile; the f16
control run the same day is clean, so the spec path itself is lossless).

### Tranche 2 — 512k 3-model anchors (bs2 GPU0, 2026-07-06)

Same harness at ctx 524288, 460k-token prompt (~424,631 tokens), q8_0-K/q4_0-V, DCA
`--dca on --dca-chunk-size 32768`, dual-ctx assistant drafter. (The anchors script's
inline curl truncated the A4B response on port-reap → false ABSENT; a clean re-probe
with `-m 3000` returned http 200, 3.0 MB body, needle PRESENT — recorded below.)

| cell | prefill t/s | decode t/s | draft accept | needle |
|---|---|---|---|---|
| A4B Q4_K_M + assistant-Q8_0, DCA on | 3211.4 | 42.3 | 0.651 (41/63) | PRESENT (re-probe) |
| 31B Q6_K + assistant-Q8_0, DCA on | 643.8 | 14.3 | 0.326 (31/95) | PRESENT |

Reading: A4B holds needle + 0.65 accept at 512k (2× native ctx via DCA), decode 42 t/s.
31B accept softens to 0.326 at 512k (its adapted drafter degrades with chunked-DCA depth)
but retrieval is intact. Both prove the fixed binary composes DCA + dual-ctx MTP + quant KV
correctly out to 512k — the regime that was 100% broken pre-fix (bug-2120 accept 0.000 or
bug-2121 corruption).

### Tranche 3 — §5b DCA niah matrix redo (bs2, in progress) + a NEW crash it surfaced

Re-running the #575 Gemma-4-A4B-v6-coder `niah_single_1` matrix (KV tiers × {256k,512k},
`--dca on --dca-chunk-size 32768`, ns=5) on the fixed binary. This is the first time these
cells have *genuinely* run DCA — pre-fix (bug-2118) the flag was a silent no-op, so the
historical "all 100.0" (§5b, #575) was DCA-**off**. Turning DCA genuinely on splits the tiers
into a clean-pass group and a crash cluster:

| tier (ctk/ctv) | ctx | niah | note |
|---|---|---|---|
| f16 / f16 | 256k | **100.0** | scalar tier — passes true DCA-on |
| q8_0 / q8_0 | 256k | **100.0** | scalar |
| q4_0 / q4_0 | 256k | **100.0** | scalar |
| q8_0 / q6_0 (q8q6asym) | 256k | **100.0** | asym scalar (q6_0 only as V) |
| q8_0 / q4_0 (q8q4asym) | 256k | **100.0** | **production tier** — matches the anchors |
| q6_0 / q6_0 | 256k | **CRASH** | bug-2125 |
| turbo3_tcq / turbo3_tcq | 256k | **100.0** | trellis-TCQ **passes** true DCA-on |
| turbo2_tcq / turbo2_tcq | 256k | **CRASH** | bug-2125 |
| turbo3_tcq K / turbo2_tcq V | 256k | **CRASH** | bug-2125 (the turbo2_tcq-V) |
| f16 / f16 | 512k | **100.0** | clean re-run — the earlier 40 was contamination; **no** DCA-depth cost at 4× native |
| q8_0 / q8_0 | 512k | **100.0** | scalar — matches 256k |
| q4_0 / q4_0 | 512k | **100.0** | scalar — matches 256k |
| q8_0 / q6_0 (q8q6asym) | 512k | **100.0** | asym scalar — matches 256k |
| q8_0 / q4_0 (q8q4asym) | 512k | **100.0** | **production tier** — holds at 4× native |
| turbo3_tcq / turbo3_tcq | 512k | **CRASH** | bug-2125 — **crashes at 512k though it PASSES at 256k** (chunk-count dependent) |
| q6_0, turbo2_tcq, t3kt2vasym | 512k | **CRASH** | bug-2125 — same crashers as 256k |

Method note: the first pass was contaminated by two runners colliding on the shared server
port (duplicate rows, one spurious q6_0=100). The table above is from the **clean single-runner**
authoritative sweep (`s5b-clean.sh`, one runner, liveness-checked boot, port reaped between
cells) — **COMPLETE** (all 9 512k cells landed 2026-07-07): the crashes are confirmed real (not
port-collision), f16-512k is 100.0, and every scalar/asym tier (f16, q8_0, q4_0, q8q6asym,
q8q4asym) holds 100.0 at 512k while the q6_0/turbo2_tcq/turbo3_tcq crash cluster is bug-2125.

**bug-2125 (NEW, exposed by the bug-2118 fix) — DCA + q6_0/turbo2_tcq KV-init segfault
(task #627, being fixed — NOT deferred).** Under real DCA, a subset of quantized tiers segfault
during context/KV-cache init (past model load + sparse-v auto-policy, at the window-tail
host-buffer setup), on `llamafile.dualctx` 91a017c8/8b23afbf, both `-fit on` and `-fit off`,
at **both 256k and 512k**: **q6_0-symmetric, turbo2_tcq-symmetric, and the turbo3_tcq-K /
turbo2_tcq-V asym** pairing all crash. The discriminator is **neither axis nor bit-count**:
**turbo3_tcq-symmetric passes 100.0** (3.25 bpv trellis on *both* K and V), and the crashing
t3kt2vasym carries a *safe* turbo3_tcq-K — so its crash is the **turbo2_tcq-V**, proving V can
trip it too. Nor is it "low bit": **q6_0 is a 6-bit scalar, hardly low-precision**, yet it
crashes while the 3.25-bpv turbo3_tcq passes. The clean split is by **specific type**: **q6_0 and
turbo2_tcq crash (on either K or V); q6_0/turbo2_tcq-free tiers pass 100.0 at 256k.** That q6_0 —
a high-precision scalar — segfaults marks this as a **genuine code defect**, not a precision floor.
**Crucially, the crash set GROWS with DCA chunk count:** turbo3_tcq **passes 100.0 at 256k (8
chunks) but CRASHES at 512k (16 chunks)**, while f16 stays clean 100.0 at both. So the trigger is
not a fixed per-type property — it scales with the number of chunks, strongly implicating a
**window-tail host-buffer whose size is mis-computed as a function of n_chunks** (a block-size /
row-alignment / dequant-on-lift assumption in the DCA chunked-rope window-tail setup that q6_0 and
turbo2_tcq block layouts violate immediately, and that turbo3_tcq only overruns once the chunk
count is high enough). None of these ever ran before (the bug-2118 contamination hid the path).
It does **not** affect the production tier (q8_0-K/q4_0-V — clean at 512k) or any shipped anchor,
but it is a real latent segfault being **root-caused + fixed under task #627** (gdb/ASAN for the
exact fault site). Historical §9/§5b turbo×DCA and q6_0×DCA cells are invalid for the same
bug-2118 reason and are superseded by this chapter.

The f16-512k number is **resolved: 100.0** (clean single-runner). The earlier 40.0 was the
two-runner contamination artifact — there is **no** DCA-depth retrieval cost for f16 at 4× native
(16 chunks). The remaining 512k scalar cells **landed 2026-07-07 all at 100.0** (q8_0, q4_0,
q8q6asym, q8q4asym) — the production tier q8_0-K/q4_0-V **holds at 4× native**. The stale note
below is retained only for history:

⚠ (superseded) The f16-512k = 40.0 reading (vs 100 at 256k) is from the possibly-contaminated first pass and
is being re-measured clean; if it holds, it is a genuine DCA-depth retrieval cost on this model
at 4× native context (16 chunks), not a bug — but treat it as provisional until the clean sweep
confirms.

### Tranche 3b — bug-2125 crash cluster RESOLVED + one NEW asym bug (bug-2141), re-measured on the WS2-shipped binary (2026-07-10)

Re-ran the Tranche-3 crash cluster on the **current shipped WS2 binary — commit `6468ae37` /
dualctx `cd65e45f` / DSO `cb8f942d`** (adds the bug-2125 fix `cbe3cf5b5` #627 + WS1 bug-2127 DCA
per-tensor defer + **WS2 in-register turbo-V DEFAULT-ON** on top of the Tranche-3 B1 binary
`91a017c8`/`8b23afbf`). Single-runner `s626-crashcells.sh`, GPU0, `--dca on --dca-chunk-size 32768`,
Gemma-4-A4B-98e-v6-coder Q4_K_M, `niah_single_1` ns=5. **The entire bug-2125 crash cluster is
CLOSED** — every previously-crashing symmetric/scalar tier now boots and retrieves 100.0:

| tier (ctk/ctv) | ctx | B1 (`8b23afbf`) | **B3 (`cb8f942d`)** | note |
|---|---|---|---|---|
| q6_0 / q6_0 | 256k | CRASH | **100.0** | bug-2125 FIXED |
| turbo2_tcq / turbo2_tcq | 256k | CRASH | **100.0** | bug-2125 FIXED |
| turbo3_tcq / turbo3_tcq | 256k | 100.0 | **100.0** | lossless-invariant (sanity) |
| turbo3_tcq K / turbo2_tcq V (asym) | 256k | CRASH | **20.0** ⚠ | now RUNS but **broken forward** — **bug-2141** |
| q6_0 / q6_0 | 512k | CRASH | **100.0** | bug-2125 FIXED |
| turbo2_tcq / turbo2_tcq | 512k | CRASH | **100.0** | bug-2125 FIXED |
| turbo3_tcq / turbo3_tcq | 512k | CRASH | **100.0** | bug-2125 FIXED (the chunk-count-dependent crash is gone) |
| turbo3_tcq K / turbo2_tcq V (asym) | 512k | CRASH | **100.0** | passes at the 16-chunk geometry (see bug-2141) |

(The scalar / asym-scalar tiers f16, q8_0, q4_0, q8q6asym, q8q4asym scored 100.0 on B1 and are
lossless-invariant under bug-2125/2127/WS2 — not re-run; they stand at 100.0 at both ctx. All
symmetric turbo/TCQ tiers now hold retrieval under genuine DCA out to 4× native.)

**Method note — re-measured on the WS2-shipped binary `6468ae37` / DSO `cb8f942d`.** Correctness
via RULER niah (never greedy); DSO deployed byte-identical at both bs2 side-load paths.

**NEW: bug-2141 — asymmetric `turbo3_tcq`-K / `turbo2_tcq`-V is broken-forward at 256k (niah 20,
4/5 EMPTY generation) but passes at 512k (100).** This is **NOT tier quality**: symmetric
`turbo2_tcq` (2-bit K+V) = 100 **and** symmetric `turbo3_tcq` = 100 at both ctx, so every
*component* of the asym cell already appears in a passing symmetric config — its K is strictly
higher-bit than the passing sym-t2 K and its V is *identical* to the passing sym-t2 V. The only
new variable is the K≠V mismatch, and the failure mode is **empty generation** (broken forward /
NaN logits), **not** wrong-answer weak retrieval. **Root cause CONFIRMED** (static trace +
GPU discriminator): under DCA-on decode `dca_fused` hardcodes `type_K=F16` (K is f16-lifted) and
dispatches the fused instance on V-type, so the asym cell is the *only* config pairing a
turbo3-derived `K_f16` with the `turbo2_tcq`-V read **in-register** (WS2 default-on) in the D512
fused kernel — a composition no symmetric control exercises. A DCA band-boundary phase whose mask
is all-`-inf` yields a zero exp-sum → 0/0 in the online-softmax normalization → NaN, which
`wht_o`'s 128-pt butterfly de-rotation (`dca.cpp:396`) smears across all 512 output lanes → empty
generation. It is **geometry-dependent** (256k/8-chunk trips the empty-band phase; 512k/16-chunk
does not) and **WS2-specific** (V f16-lift scored 60, functional; the WS2 in-register flip
regressed it to 20). **Decisive discriminator (bs2 GPU0, same binary):** asym @256k DCA-on with
`WS2_DCA_TURBO_V=0` → **niah 100.0 / 0 empty** (vs WS2 default-on **20.0 / 4 empty**) — forcing V
back to the f16-lift path (same K-lift) fully recovers, proving the fault is the **WS2
in-register-V + `wht_o` composition**, not the K-lift or any codebook. (All per-tensor
type/codebook selection was verified correct by static trace; the stringly-typed `cache_k_`/`cache_v_`
split gates only a 4% norm-alpha and cannot NaN.) **Escape hatch that works today:**
`WS2_DCA_TURBO_V=0` for asym turbo_tcq K≠V. Fix directions: (1) NaN-safe the online-softmax
normalization for all-`-inf` DCA band phases before `wht_o` (principled; keeps the WS2 win), or
(2) gate WS2 in-register-V off for asym turbo_tcq K≠V. **Quarantine both asym-turbo_tcq directions
pending the fix; the production tier q8_0-K/q4_0-V is unaffected** (clean 100.0 at 256k and 512k).
Full RCA in `.wolf/buglog.json` bug-2141.

**Direction-specific (not symmetric).** The reverse asym `turbo2_tcq`-K / `turbo3_tcq`-V @256k
scored **100.0 / 0-empty** — clean. So the break is confined to the **`turbo3_tcq`-K + `turbo2_tcq`-V**
ordering at the 256k/8-chunk geometry: it needs the *higher-precision* turbo3-K_f16 (sharper KQ
logits, which is what drives a band phase to the all-`-inf` boundary) paired with the
turbo2-V-in-register instance. The reverse ordering (turbo2-K_f16 + turbo3-V-in-register) does not
produce the boundary condition, and both symmetric configs are clean — consistent with the
uniquely-uncovered-composition thesis. Confirmed cells (256k, DCA-on, ns=5): t3K/t2V = **20**
(4/5 empty), t3K/t2V `WS2_DCA_TURBO_V=0` = **100**, t2K/t3V = **100**, sym-t2 = **100**,
sym-t3 = **100**. Recommendation: prefer the escape hatch or avoid the t3K/t2V pairing under DCA
until the NaN-safe fix lands; production tier q8_0-K/q4_0-V is unaffected.

### bug-2121 formal correctness gate (14B-1M q8K/q4V, window-mode host tail)

Beyond the greedy-needle deep-spill gate (tails 1600/3200/6400 all PRESENT, zero crashes),
a semantic `niah_single_1` gate (ns=5) on Qwen2.5-14B-1M q8_0-K/q4_0-V compares window mode
with a forced multi-tile host tail (≥2 tail tiles) against the fully-resident control:

| config | niah | note |
|---|---|---|
| resident (control) | **100.0** | reference — all 5 samples finish=stop, correct needle |
| window, deep tail (256/80128 resident ≈ **2.44 tail tiles**), max_tokens=24 | **100.0** | **clean pass** — genuine ≥2-tile spill, needle retrieved every sample |

**Verdict: the clean ns=5 gate PASSES — #625 CLOSED.** The earlier "tail 3200 = 40.0"
reading was a **harness artifact, not a defect.** The original gate used max_tokens=120, so
some tail-region needles rambled to the token cap (finish=length) instead of retrieving and
stopping — 2/5 correct, 2/5 ramble, 1/5 truncate = 40 — a *scoring* confound, not the pre-fix
corruption signature (no GPFs, no garbage, no crash; decode was normal deep-spill ~0.6–1.6 tps,
and an earlier "159–400 s/token" reading was just a misread of `gen_secs`, which includes the
~1307 s prefill). Re-running the **same deep-spill config with max_tokens=24** (so a
correct-but-verbose sample can't be mis-scored) and a forced **2.44-tile** host tail — deeper
than the original — the window path scores **100.0, identical to the fully-resident control.**

So the bug-2121 window path is clean at genuine multi-tile deep spill, corroborating the
single-forward basis that already validated the fix: the greedy-needle deep-spill gate (tails
1600/3200/6400 all **PRESENT**, zero crashes/GPFs), teacher-forced **logit-equiv real_frac=0**,
and the 35B NextN tail-collateral recovery (0.449→0.625, below). The prefill-corruption defect
bug-2121 targeted is gone by every measure — single-forward and now a clean multi-request niah.

### Collateral: 35B NextN tail=200 accept recovery (confirms bug-2121 reach)

The pre-fix 35B-A3B NextN spill-decode anomaly — tail=200 accept dropping to 0.449 while
tail=0 held 0.606 — recovered to **0.625** on the fixed DSO (8b23afbf) with the tail=0
control unchanged at 0.606 (same calibration). So the cross-stream pool aliasing (bug-2121)
was also silently corrupting that draft path; the fix repairs it. (buglog bug-2121 collateral.)

### Tranche 4 — anchor + MTP×DCA re-validation on the WS2-shipped binary (2026-07-10)

Re-ran the Tranche-1/2 anchors **and** the §8 Gemma MTP×DCA logit-equivalence gate on the
**current shipped binary — commit `6468ae37` / dualctx `cd65e45f` / DSO `cb8f942d`** (bug-2125 fix
+ WS1 bug-2127 + WS2 default-on), GPU0 (`tier23-master.sh`), `--dca on --dca-chunk-size 32768`.

**(a) Correctness re-validated — accept + needle are byte-stable B1 → B3.** Every anchor's draft
acceptance and needle match the Tranche-1/2 (B1 `8b23afbf`) values exactly, on the genuinely-DCA-on
WS2 binary:

| cell | ctx | accept B1 → **B3** | needle | prefill tok/s B1 → **B3** |
|---|---|---|---|---|
| A4B Q4_K_M + assistant-Q8_0, DCA on | 256k | 0.700 → **0.700** (42/60) | PRESENT | 5200 → **5188** (parity) |
| 31B Q6_K + assistant-Q8_0, DCA on | 256k | 0.456 → **0.4557** (36/79) | PRESENT | 1149 → **1147** (parity) |
| Qwen3.6-35B UD-Q6_K NextN (no DCA) | 256k | 0.606 → **0.606** (40/66) | PRESENT | 2812 → **2428** ⚠ (contention) |
| A4B Q4_K_M + assistant-Q8_0, DCA on | 512k | 0.651 → **0.651** (41/63) | PRESENT | 3211 → **3208** (parity) |
| 31B Q6_K + assistant-Q8_0, DCA on | 512k | 0.326 → **0.326** (31/95) | PRESENT | 644 → **642** (parity) |

So MTP×DCA + dual-ctx drafters compose correctly and byte-stably on the shipped WS2 binary; the
A4B/31B **prefill** tok/s are at parity with B1 (no prefill regression).

**(b) Decode tok/s — DEFERRED, cross-GPU contention (not recorded as corrected values).** These
anchors ran while GPU1 was committed to task #631's spill sweep, and the cerebrum rule holds:
**tps cannot be trusted with the sibling GPU busy** (PCIe/host-BW contention). The observed B3
decode numbers came in **uniformly ~15–30 % below B1 across all cells — including the no-DCA Qwen
NextN control** (a change in a non-DCA path that no WS2/bug-2127 edit touches), the tell-tale
signature of contention, not a code change. (Prefill, being compute-bound, held parity; decode,
the PCIe-sensitive phase, is the one that sagged.) **The manifest's "bug-2127 ~2× decode
understatement" premise does not apply to these cells anyway** — bug-2127's ~2× win is the
**asym scalar-K + turbo-V** decode path; these anchors are q8_0-K/**q4_0-V (scalar V)**, so neither
bug-2127 nor WS2-in-register-turbo-V engages. **A clean DCA-on decode-tps re-measure is deferred to
when GPU1 (#631) is idle** and should be run serially with the sibling GPU idle. (The DCA-on
turbo/TCQ-V decode win that WS2 *does* deliver is already the §5x matrix.)

**(c) §8 Gemma assistant-MTP × DCA @256k real_frac — RE-CONFIRMED (bug-2118 fix).** The #431
logit-equivalence gate (ref = plain DCA-on, cand = `--spec-type draft-assistant` DCA-on, both
`--dca-chunk-size 32768`, google 26B-A4B-128e Q4_K_M + drafters-hf assistant Q8_0, teacher-forced
top-20) now runs with **genuine** DCA (bug-2118 made it a no-op when §8 was first logged):
**`real_frac = 0.0`, `real_disagreements = 0`, `frac_full_agree = 1.0`** → **PASS**. So Gemma
assistant-MTP verify is bit-equivalent to plain decode over DCA-laid-out KV at 256k on the shipped
binary — the §8 claim stands, now on real DCA. (The runner's `mean_tv_advisory ≈ 0.44` "VERDICT:
FAIL" is the documented empty-top-logprobs artifact for spec-accepted tokens — `real_frac` is the
gate, and the runner emitted `W4_GEMMA_DCA256K_PASS`.) Harness `tier3-mtp-dca-b3.sh`.

**GPU0 CLEAR after this tranche** (servers reaped by port); decode-tps re-measure pending GPU1 idle.

### Tranche 5 — #674: DCA-OFF scalar-quant MMA decode generalized to Gemma D256/D512 (bs2 GPU1, 2026-07-14)

Folds the #674 result into this campaign. This is **not** a DCA cell — it's the DCA-**off** high-VRAM
serving path (scalar-quant KV over the tensor-core MMA decode kernel, patch 0127, chain→73), the
D256(SWA-local)/D512(global) generalization of the #620 D128 lever that §3b (Tier-1) folded for Qwen.
Gemma-4 A4B native (google 26B-A4B-128e Q4_K_M), DCA-off, decode-tps + logit-equiv vs f16 (Gemma PPL
is garbage → correctness is top-token identity, `real_frac`):

| ctx | nkv | f16 | q4q4 | q8q8 | q8q4 | q8q4 vs f16 | env=0 VEC | real_frac |
|-----|-----|-----|------|------|------|-------------|-----------|-----------|
| 64k  | 42.5k | 162.13 | 170.17 | 173.86 | **174.94** | **+7.9%** | 122.17 (MMA +43% over VEC) | 0.0 |
| 128k | 112k  | 152.15 | 152.95 | —      | **154.46** | **+1.5%** | (§3c had q8q4-VEC −35% here) | 0.0 |

**Verdict:** scalar-quant KV now **beats f16 and is top-token-lossless** at both depths on Gemma's
D256+D512 — so with enough VRAM it is the **preferred serving path over turbo** (turbo is slower AND
lower quality). The §3c/§3d kernel-bound quant tax (−28…−35% at long ctx) is **erased**; the win
narrows deep (MoE-FFN + per-step launch dilute the KV-bandwidth delta) but stays ≥ f16. env
`OPENCOTI_QUANT_MMA_DECODE=0` reverts each pair to its native FA-VEC route at every head-dim (graceful).
Build note: the 20 D512-heavy instances push `ggml-cuda.so` to 4.43 GiB → bug-2178 (streamed
`sha256OfFile`). Tax-erasure detail in `hal_kv_compression.md` §3c. **256k cell intentionally skipped**
— the curve is monotone toward the f16 floor (parity), not a cliff, so it adds no serving-guidance signal.

### Tranche 6 — Tier-1 spill + Tier-2 short cells on the fixed binary (bs2, 2026-07-12)

The remaining #654 re-run cells (binary `7abd684039a3` / DSO `1d8fe395c53a`, greedy, `cache_prompt=false`,
`n_predict` 256–300, `--kv-residency-mode window --vram-target 90000`). All decode-tps single-GPU
(no sibling contention this batch). Closes the campaign apart from two harness slips noted below.

**Tier-1 — Gemma/Qwen spill decode @256k/512k** (q8_0-K/q4_0-V, needle probe):

| model | ctx | decode tps | needle |
|-------|-----|-----------|--------|
| A4B (google 26B-128e) | 256k | 114.75 | PRESENT |
| A4B | 512k | 68.00 | PRESENT |
| Gemma-31B | 256k | 33.34 | PRESENT |
| Gemma-31B | 512k | 23.24 | PRESENT |
| Qwen3.6-35B-A3B NextN | 256k | 151.53 | PRESENT |

**Tier-2 short cells:**
- **§3.0a — A4B MTP×KV-tier decode (turbo/TCQ), f16 anchor** (decode tps, off → on / accept): f16 200.4 →
  **365.8** (0.984); turbo3 153.1 → **263.8** (0.984); turbo3_tcq 104.7 → **214.7** (0.990). MTP self-spec
  ~1.4–1.8× decode across every KV tier; turbo/TCQ stay accept-lossless (≥0.98).
- **§2a — 3-arm DCA on/off prefill×gen** (A4B / Gemma-31B, prefill → gen tps): A4B off 6412 → 156.7, on
  7708 → 142.6; Gemma-31B off 2017 → 36.5, on 2121 → 35.7. DCA prefill even edges up on A4B (chunked
  attn), decode within noise — no DCA tax.
- **§4c — NIAH q8_0/q8_0** 16k/32k/64k/128k all **100.0** (n=5). **real_frac gate** (assistant-MTP vs
  plain, DCA-off): **`real_frac=0.0`, `frac_full_agree=1.0` → PASS** (the runner "FAIL" is the documented
  empty-top artifact; `mean_tv_advisory` is advisory only).

**Two harness slips (not engine regressions):**
1. **short4 fused-nextn ours BOOT-FAIL → FIXED + re-run (2026-07-14).** The `run()` boot line omitted
   `--server`, so ours (llamafile) came up in CLI **chat** mode and never answered `/health`; b9859
   (upstream `llama-server`) is a server by default so it booted (bug-2179). Fixed (conditional
   `--server` for ours) and re-run on GPU1: ours base **208.3** (≈ b9859 212.0, parity), n1 **226.4**/acc
   0.892, n2 **230.4**/0.739, n3 **240.1**/0.638 — NextN decode trails b9859 by ~12–15 % (the unchanged
   bug-858 verify/CUDA-graph gap, accept at/above upstream at n1). Full table in `fused_nextn_mtp.md`.
2. **tier1-gpuB t2 @512k Qwen-NextN parse-fail** — server booted fine (KV fully resident) but the warmup
   **prompt (435,574 tok) exceeded the available per-request context (262,144)** → `send_error`, which the
   harness' JSON parse choked on. This is per-sequence context halving under the dual-context `draft-mtp`
   path at 512k (`ctx_tgt`+`ctx_dft` split), not a crash; the t1 @256k cell is clean (151.53, PRESENT).
   The Tranche-2 512k Qwen-NextN cell is **optional** — re-run needs a prompt sized to n_ctx/2, or `-c 1M`.