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GLM-5.3-Flash-REAP50-FP8

Safetensors
glm5_next
reap
Mixture of Experts
pruning
jetson
thor
fp8
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  1. README.md +26 -1
  2. model-00003-of-00062.safetensors +1 -1
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README.md CHANGED
@@ -6,6 +6,31 @@ tags: [reap, moe, pruning, glm5_next, jetson, thor]
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  # GLM-5.3-Flash REAP-50 (FP8)
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  50% of routed experts removed with **REAP**
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  (Router-weighted Expert Activation Pruning, arXiv:2510.13999), calibrated on a
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  permissively-licensed multi-domain corpus that includes real image-text pairs.
@@ -15,7 +40,7 @@ permissively-licensed multi-domain corpus that includes real image-text pairs.
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  | Base | `zai-org/GLM-5.3-Flash` (MIT, FP8 E4M3, 128x128 block scales) |
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  | Experts | 288 -> 144 per layer, top-8 routing unchanged |
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  | Size | 157.0 GiB (FP8) |
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- | Healed | yes |
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  | MTP block | excluded (see below) |
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  ## Why FP8 and not BF16
 
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  # GLM-5.3-Flash REAP-50 (FP8)
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+ > ## Corrected 2026-08-28 — healing scalar re-fit
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+ >
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+ > **This checkpoint has been revised.** The original upload applied a first-moment healing gain
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+ > (median **0.6933**) to every retained expert's output. That estimator ignores that
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+ > `norm_topk_prob` renormalises the surviving top-8, so the router already returns essentially all
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+ > the pruned gate mass by itself — **measured: gate mass 2.5000 before pruning and 2.5000 after**.
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+ > The derivation therefore prescribed a ~39% shrink where the true output inflation is ~10%.
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+ >
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+ > Re-measured by replaying post-prune routing from a cached router-score trace over 2.3M tokens,
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+ > the correct gain is median **0.9111** (per-layer 0.846–0.950).
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+ > Every layer's block scales have been multiplied by `measured / shipped`
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+ > (median **1.3121**, range 1.0719–1.5260), correcting a systematic
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+ > under-scaling of the entire MoE pathway relative to attention, the shared experts and the
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+ > residual stream.
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+ >
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+ > The fix is exact and lossless: it scales the F32 `weight_scale_inv` tensors, never the FP8
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+ > values, so no weight was requantised. 6,048 block scales were corrected — exactly
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+ > 42 layers x 144 retained experts.
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+ >
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+ > **If you downloaded the earlier revision, re-pull.** The previous state remains in this repo's
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+ > git history, and is recoverable by dividing the block scales by the factors above.
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+ >
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+ > Not yet propagated to the NVFP4 sibling repo, which still carries the original gain.
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+
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+
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  50% of routed experts removed with **REAP**
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  (Router-weighted Expert Activation Pruning, arXiv:2510.13999), calibrated on a
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  permissively-licensed multi-domain corpus that includes real image-text pairs.
 
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  | Base | `zai-org/GLM-5.3-Flash` (MIT, FP8 E4M3, 128x128 block scales) |
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  | Experts | 288 -> 144 per layer, top-8 routing unchanged |
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  | Size | 157.0 GiB (FP8) |
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+ | Healed | yes — **re-fit 2026-08-28**, measured gain 0.9111 |
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  | MTP block | excluded (see below) |
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  ## Why FP8 and not BF16
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