Upload 920 files

.gitattributes

@@ -1,60 +1,3 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.avro filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.lz4 filter=lfs diff=lfs merge=lfs -text
-*.mds filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
-# Audio files - uncompressed
-*.pcm filter=lfs diff=lfs merge=lfs -text
-*.sam filter=lfs diff=lfs merge=lfs -text
-*.raw filter=lfs diff=lfs merge=lfs -text
-# Audio files - compressed
-*.aac filter=lfs diff=lfs merge=lfs -text
-*.flac filter=lfs diff=lfs merge=lfs -text
-*.mp3 filter=lfs diff=lfs merge=lfs -text
-*.ogg filter=lfs diff=lfs merge=lfs -text
-*.wav filter=lfs diff=lfs merge=lfs -text
-# Image files - uncompressed
-*.bmp filter=lfs diff=lfs merge=lfs -text
-*.gif filter=lfs diff=lfs merge=lfs -text
-*.png filter=lfs diff=lfs merge=lfs -text
-*.tiff filter=lfs diff=lfs merge=lfs -text
-# Image files - compressed
-*.jpg filter=lfs diff=lfs merge=lfs -text
-*.jpeg filter=lfs diff=lfs merge=lfs -text
-*.webp filter=lfs diff=lfs merge=lfs -text
-# Video files - compressed
-*.mp4 filter=lfs diff=lfs merge=lfs -text
-*.webm filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,14 @@
+**/__pycache__/
+*.py[cod]
+**/.vendor/
+**/.cache/
+**/cache/
+**/logs/
+**/comfy_output/
+**/results/
+*.safetensors
+*.ckpt
+*.gguf
+.env
+.env.*
+!*.example

CITATION.cff

@@ -0,0 +1,9 @@
+cff-version: 1.2.0
+message: If you use this benchmark, please cite it.
+title: Krea 2 Turbo ComfyUI Format Fidelity Benchmark
+type: dataset
+version: 1.0.0
+date-released: 2026-07-13
+authors:
+  - name: Krea 2 Turbo Formats Benchmark Contributors
+license: CC-BY-4.0

LICENSE-CODE

@@ -0,0 +1,9 @@
+MIT License
+
+Copyright (c) 2026 Krea 2 Turbo Formats Benchmark Contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

LICENSE-DATA

@@ -0,0 +1,5 @@
+Creative Commons Attribution 4.0 International (CC BY 4.0)
+
+Copyright (c) 2026 Krea 2 Turbo Formats Benchmark Contributors
+
+This work is licensed under the Creative Commons Attribution 4.0 International License. To view the complete legal code, visit https://creativecommons.org/licenses/by/4.0/legalcode .

README.md

@@ -1,3 +1,98 @@
----
-license: mit
----
+---
+language:
+- en
+license: cc-by-4.0
+pretty_name: Krea 2 Turbo ComfyUI Format Fidelity Benchmark
+size_categories:
+- n<1K
+task_categories:
+- text-to-image
+tags:
+- image
+- tabular
+- comfyui
+- krea-2
+- quantization
+- benchmark
+- bf16
+- fp8
+- int8
+- mxfp8
+- nvfp4
+---
+
+# Krea 2 Turbo ComfyUI Format Fidelity Benchmark
+
+This release is a paired, deterministic comparison of the BF16, FP8 Scaled, INT8 ConvRot, MXFP8, and NVFP4 Krea 2 Turbo checkpoints through native ComfyUI execution. It contains 150 scored 1024×1024 images, all saved float32 decoded tensors and final latents, every denoising trajectory, raw metric tables, scored telemetry, statistical comparisons, and reproducibility code.
+
+![Five-format contact sheet](comparison_sheets/contact_sheet_replicate0.png)
+
+## Main result
+
+1. **BF16** is the highest-fidelity reference because it is the unquantized published checkpoint.
+2. **INT8 ConvRot** is the best quantized checkpoint by the preregistered LPIPS-Alex endpoint and also leads the other quantized formats on DISTS, DINO similarity, final-latent relative L2, and reconstructed-weight SNR.
+3. **MXFP8** ranks second among quantized formats for fidelity on this campaign.
+4. **FP8 Scaled** ranks third among quantized formats.
+5. **NVFP4** is the smallest checkpoint, but it has the largest measured fidelity loss.
+
+No weighted composite score is used. See [the full technical report](TECHNICAL_REPORT.md) and [`tables/decision_table.csv`](tables/decision_table.csv).
+
+## Important performance limitation
+
+The test GPU was an NVIDIA GeForce RTX 4060 Ti 16 GB (SM 8.9). In the tested ComfyUI/comfy-kitchen runtime, MXFP8 and NVFP4 native fast matrix multiplication requires SM 10.0, so their measured Ada timings used fallback/dequantized execution and must not be projected to Blackwell hardware.
+
+## Dataset organization
+
+- `data/train/metadata.jsonl` is the Hugging Face ImageFolder index. Each row links an image to its prompt, seed, format, checkpoint provenance, raw scientific artifacts, and flattened metric values.
+- `raw/` contains `decoded_float32.npy`, `final_latent_float32.npy`, `trajectory.npz`, and capture `metadata.json` for every scored run.
+- `metrics/` contains raw per-image, per-parameter, paired-statistics, summary, trajectory, latency, and performance tables.
+- `comparison_sheets/` contains five-format sheets, BF16-relative difference maps, and automatically selected detail crops.
+- `telemetry/` contains only scored GPU and system telemetry.
+- `provenance/` contains sanitized environment, model, run, and release manifests.
+- `reproduction/` contains the ComfyUI workflows, custom capture node, benchmark driver, analyzers, model downloader, and exact instructions.
+
+Load the image table locally:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("imagefolder", data_dir="data", split="train")
+print(dataset.num_rows)  # 150
+```
+
+## Fixed inference controls
+
+- 15 prompts × 2 deterministic seeds × 5 checkpoint formats = 150 scored images
+- 1024×1024, batch size 1
+- 8 steps, CFG 1.0, Euler sampler, simple scheduler, denoise 1.0
+- Shared `qwen3vl_4b_bf16.safetensors` text encoder and `qwen_image_vae.safetensors` VAE
+- Zeroed positive conditioning used as negative conditioning
+- No prompt rewriting, LoRAs, previews, upscaling, or post-processing
+- Identical initial-noise SHA-256 for every five-format prompt/seed group
+
+## Reproduce or verify
+
+Follow [`reproduction/README.md`](reproduction/README.md). A faithful full rerun downloads 77.536 GiB of upstream model files and should have at least 110 GiB of free disk space. The published benchmark was tested on Windows 11 with a 16 GB NVIDIA GPU; lower-memory configurations are not certified.
+
+Validate this downloaded release:
+
+```bash
+python scripts/validate_release.py --root . --full
+```
+
+Upload a locally rebuilt copy:
+
+```bash
+hf auth login
+python scripts/upload_to_huggingface.py OWNER/DATASET --root .
+```
+
+## Licenses and responsible use
+
+Generated images, data, and reports are released under CC BY 4.0. Benchmark scripts are MIT licensed. Model weights are not redistributed and remain governed by the Krea 2 Community License. Krea states that it does not claim intellectual-property rights over user-generated outputs, while users remain responsible for their prompts, outputs, and downstream use. Review the [official Krea 2 Turbo model card and license](https://huggingface.co/krea/Krea-2-Turbo) before downloading or running the checkpoints.
+
+The prompt suite avoids requests for real people, explicit content, unlawful activity, or protected logos. Generated images can still contain model errors, stereotypes, malformed text, or unintended resemblance. This benchmark evaluates checkpoint fidelity on one controlled campaign; it is not a universal ranking of human aesthetic preference or all hardware.
+
+## Citation
+
+See [`CITATION.cff`](CITATION.cff). The project attribution name is **Krea 2 Turbo Formats Benchmark Contributors**.

TECHNICAL_REPORT.md

@@ -0,0 +1,249 @@
+# Krea 2 Turbo Checkpoint-Format Benchmark
+
+> This report is generated from the saved raw tensors, trajectories, telemetry, and metric tables. No result is inferred from filename or nominal bit width.
+
+## Executive conclusion
+
+- **Highest model fidelity:** BF16, because it is the unquantized reference checkpoint used for all paired comparisons.
+- **Best quantized BF16 fidelity by the preregistered primary endpoint (LPIPS-Alex):** INT8 ConvRot.
+- **Primary-endpoint separation from the next quantized format:** statistically separated after Holm correction.
+- **Smallest checkpoint:** NVFP4.
+- **Ada performance warning:** MXFP8 and NVFP4 use fallback/dequantized matrix multiplication on this SM 8.9 GPU; their recorded speed must not be projected to Blackwell hardware.
+- Automated results establish original-model fidelity, prompt alignment, and measurable artifact behavior. They do not establish universal human aesthetic preference.
+
+### Decision table
+
+| Format | File GiB | LPIPS↓ | DISTS↓ | DINO cosine↑ | Final latent rel-L2↓ | Weight SNR dB↑ | Sampling s↓ | Peak VRAM MiB↓ | Energy J↓ |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| BF16 | 24.478 | 0.000000 | 0.000000 | 1.000000 | 0.000000 | n/a | 25.783 | 15221.0 | 3656.0 |
+| FP8 Scaled | 12.239 | 0.093701 | 0.042738 | 0.971012 | 0.223618 | 31.585775 | 19.503 | 14397.0 | 3013.5 |
+| INT8 ConvRot | 12.566 | 0.041864 | 0.026796 | 0.983833 | 0.132571 | 41.157030 | 12.417 | 15165.0 | 1944.8 |
+| MXFP8 | 12.603 | 0.071229 | 0.035132 | 0.979443 | 0.201900 | 31.604820 | 31.929 | 14750.0 | 4142.8 |
+| NVFP4 | 7.147 | 0.205124 | 0.084436 | 0.934769 | 0.381361 | 20.600707 | 24.925 | 14459.0 | 3679.3 |
+
+The decision table is multidimensional by design. No weighted composite score is used.
+
+## Test system and immutable controls
+
+- GPU: `NVIDIA GeForce RTX 4060 Ti; driver 610.74; 16380 MiB; compute capability 8.9`
+- ComfyUI commit: `917faef771a2fd2f14f44af94f17da3d0b2803a3` (2026-07-12T09:43:30-07:00)
+- PyTorch: `2.13.0+cu130`; CUDA runtime: `13.0`; comfy-kitchen: `0.2.18`
+- Python: `3.13.12 (tags/v3.13.12:1cbe481, Feb  3 2026, 18:22:25) [MSC v.1944 64 bit (AMD64)]`
+- Resolution: 1024×1024; batch size 1
+- Sampler: euler; scheduler: simple; steps: 8; CFG: 1.0; denoise: 1.0
+- Shared text encoder: `qwen3vl_4b_bf16.safetensors`; shared VAE: `qwen_image_vae.safetensors`
+- Negative conditioning is a zeroed copy of positive conditioning. Prompt rewriting, LoRAs, previews, upscaling, and post-processing are disabled.
+- Each prompt/seed pair uses the same initial-noise tensor SHA-256 across all five formats.
+
+## Checkpoint structure
+
+| Format | File | SHA-256 | GiB | Tensors | Stored dtypes | Metadata |
+| --- | --- | --- | --- | --- | --- | --- |
+| BF16 | krea2_turbo_bf16.safetensors | 78bbf8f4165eda19cea3cb06c78089221932a39e2eed8af9da741f942c47ffb3 | 24.478 | 430 | BF16: 256<br>F32: 174 | none |
+| FP8 Scaled | krea2_turbo_fp8_scaled.safetensors | eb4dd8c612cfd10f64f25b057e6e6bbcb5737c94a7372177e456dbf7579502f1 | 12.239 | 686 | BF16: 174<br>F32: 256<br>F8_E4M3: 256 | _quantization_metadata, format |
+| INT8 ConvRot | krea2_turbo_int8_convrot.safetensors | 8e4eeda70dd5037ab1ba2bef6b417f9f901e26093117cf397f741fc1fdaaf3f1 | 12.566 | 878 | BF16: 76<br>F32: 354<br>I8: 224<br>U8: 224 | none |
+| MXFP8 | krea2_turbo_mxfp8.safetensors | 4c09131a442c3a01e95f934b43c76c1e691b9f683694a7b68d6fc707d5ecfce3 | 12.603 | 686 | BF16: 174<br>F8_E4M3: 256<br>U8: 256 | _quantization_metadata, format |
+| NVFP4 | krea2_turbo_nvfp4.safetensors | 61527003b2d537055494d01bc8efe51d6e86e64192ba23e3721a5647231fe394 | 7.147 | 942 | BF16: 174<br>F32: 256<br>F8_E4M3: 256<br>U8: 256 | _quantization_metadata, format |
+
+### What the formats actually do
+
+- **BF16 reference:** main matrix weights are BF16 while several norms/scales are stored as FP32. It preserves the published parameter values but exceeds the 16 GB VRAM capacity and therefore requires offloading.
+- **FP8 Scaled:** E4M3 weights plus explicit tensor scales. The checkpoint marks 256 linear layers, including 96 linears configured for full-precision matrix multiplication and 160 eligible for quantized multiplication.
+- **INT8 ConvRot:** 224 row-wise INT8 linear weights with group-size-256 online/offline Hadamard rotation. Sensitive input/output, conditioning, and text-fusion components remain higher precision.
+- **MXFP8:** E4M3 values with E8M0 power-of-two block scales over 32-element blocks. It marks 256 linear layers; native fast multiplication requires SM 10.0 in this runtime.
+- **NVFP4:** packed 4-bit floating-point values with per-tensor and 16-element block scales. It marks 256 linear layers; native fast multiplication likewise requires SM 10.0.
+
+## Weight reconstruction fidelity
+
+Every logical parameter was reconstructed with the same native comfy-kitchen layout used at inference and streamed against the BF16 safetensors reference. Aggregates are element weighted; unchanged high-precision tensors are included.
+
+| Format | Logical tensors | Quantized tensors | MAE | RMSE | Relative L2 | Cosine | SNR dB | Max abs |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| BF16 | 430 | 0 | 0.000000 | 0.000000 | 0.000000 | 1.000000000 | n/a | 0.000000 |
+| FP8 Scaled | 430 | 256 | 0.000722 | 0.001166 | 0.026346 | 0.999652901 | 31.586 | 0.187500 |
+| INT8 ConvRot | 430 | 224 | 0.000277 | 0.000387 | 0.008753 | 0.999961693 | 41.157 | 0.091442 |
+| MXFP8 | 430 | 256 | 0.000721 | 0.001163 | 0.026288 | 0.999654434 | 31.605 | 0.250000 |
+| NVFP4 | 430 | 256 | 0.002923 | 0.004129 | 0.093318 | 0.995646025 | 20.601 | 0.531250 |
+
+Full per-parameter results, including p50/p95/p99/p99.9 error samples and subsystem grouping, are in [`metrics/weight_parameters_all.csv`](metrics/weight_parameters_all.csv).
+
+## Paired image fidelity
+
+BF16 is a behavioral reference, not a real photograph. Low LPIPS/DISTS and high DINO/SSIM indicate that a quantized checkpoint follows the BF16 generation trajectory more closely; they do not independently prove a more attractive image.
+
+| Format | LPIPS Alex↓ | LPIPS VGG↓ | DISTS↓ | MS-SSIM↑ | DINO cosine↑ | SSIM RGB↑ | ΔE2000↓ |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| BF16 | 0.000000 | 0.000000 | 0.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000000 |
+| FP8 Scaled | 0.093701 | 0.095434 | 0.042738 | 0.869319 | 0.971012 | 0.874324 | 2.588693 |
+| INT8 ConvRot | 0.041864 | 0.050027 | 0.026796 | 0.956164 | 0.983833 | 0.948027 | 1.234503 |
+| MXFP8 | 0.071229 | 0.094774 | 0.035132 | 0.917225 | 0.979443 | 0.901653 | 2.643008 |
+| NVFP4 | 0.205124 | 0.223690 | 0.084436 | 0.768737 | 0.934769 | 0.796323 | 6.313444 |
+
+Statistics use 50,000 prompt-cluster BCa bootstrap resamples. Quantized-format pairwise tests use all 2^15 exact prompt-level sign permutations with Holm correction across the six pairs per metric.
+
+## Prompt adherence and no-reference quality
+
+| Format | CLIPScore↑ | PickScore↑ | HPSv2↑ | MUSIQ↑ | MANIQA↑ | TOPIQ-NR↑ | NIQE↓ | BRISQUE↓ |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| BF16 | 41.327330 | 22.496188 | 0.287720 | 71.562683 | 0.464503 | 0.596940 | 4.279002 | 25.846741 |
+| FP8 Scaled | 41.257368 | 22.677390 | 0.285767 | 72.232819 | 0.460313 | 0.598193 | 4.447991 | 25.120178 |
+| INT8 ConvRot | 41.762024 | 22.668381 | 0.288574 | 70.952457 | 0.458785 | 0.596355 | 4.369028 | 26.581604 |
+| MXFP8 | 41.587543 | 22.493693 | 0.289673 | 72.054489 | 0.463579 | 0.594426 | 4.395214 | 25.064392 |
+| NVFP4 | 41.326290 | 22.693707 | 0.285645 | 69.801792 | 0.479385 | 0.591738 | 4.430767 | 26.218567 |
+
+These models have different training biases, particularly on illustration and typography. They are reported independently and are never averaged into a single score.
+
+### OCR on prompts with required text
+
+| Format | Images | Exact target fraction↑ | Median exact fraction↑ | Normalized edit distance↓ | OCR confidence↑ | Recognized lines |
+| --- | --- | --- | --- | --- | --- | --- |
+| BF16 | 6 | 0.611111 | 0.666667 | 0.138889 | 0.764390 | 4.67 |
+| FP8 Scaled | 6 | 0.555556 | 0.500000 | 0.145062 | 0.781645 | 4.33 |
+| INT8 ConvRot | 6 | 0.666667 | 0.666667 | 0.133333 | 0.763667 | 4.67 |
+| MXFP8 | 6 | 0.611111 | 0.666667 | 0.157265 | 0.759152 | 4.50 |
+| NVFP4 | 6 | 0.611111 | 0.666667 | 0.152381 | 0.780622 | 4.67 |
+
+OCR is evaluated only on the six package/storefront/scientific-poster images per format. Exact target fraction is the share of requested phrases found verbatim after uppercase normalization.
+
+## Denoising trajectory
+
+The sampler saved both current latent `x` and predicted denoised state `x0` after every one of the eight free-running steps. The trajectory tables include relative L2, cosine, spectrum-relative L2, non-finite counts, and final latent divergence. Because each format consumes its own preceding output, later-step error includes accumulated trajectory divergence and is not a teacher-forced layer error.
+
+See [`metrics/trajectory.csv`](metrics/trajectory.csv) and [`metrics/image_core.csv`](metrics/image_core.csv).
+
+## Artifact detectors
+
+For every float decoded image the analysis records clipping, gradient distribution, flat-region banding proxies, chroma noise, Laplacian energy, high-frequency spectral power, 8/16/32-pixel grid-boundary energy, luminance, saturation, and BF16-relative edge/color drift. These diagnostics identify where to inspect; none is treated as an aesthetic score by itself.
+
+## Runtime, memory, and energy on RTX 4060 Ti
+
+| Format | End-to-end s | Sampling s | VAE s | Peak VRAM MiB | Peak process RAM GiB | Mean W | Energy J | Peak °C |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| BF16 | 27.154 | 25.783 | 0.360 | 15221.0 | 14.161 | 134.1 | 3656.0 | 71.0 |
+| FP8 Scaled | 20.921 | 19.503 | 0.344 | 14397.0 | 2.278 | 143.8 | 3013.5 | 73.0 |
+| INT8 ConvRot | 13.623 | 12.417 | 0.356 | 15165.0 | 2.309 | 141.7 | 1944.8 | 72.0 |
+| MXFP8 | 33.244 | 31.929 | 0.345 | 14750.0 | 4.507 | 124.3 | 4142.8 | 69.0 |
+| NVFP4 | 26.391 | 24.925 | 0.345 | 14459.0 | 3.730 | 139.0 | 3679.3 | 71.0 |
+
+Latency summaries use 30 scored runs per format after three repeatability/warmup executions. GPU and system telemetry were sampled every 100 ms. Model-load and warmup records remain available in `runs.jsonl` and telemetry files but are excluded from steady-state medians.
+
+## Comparison sheets
+
+- [Master contact sheet](comparison_sheets/contact_sheet_replicate0.png)
+- [`comparison_sheets/full/`](comparison_sheets/full/) — labeled five-format images
+- [`comparison_sheets/details/`](comparison_sheets/details/) — three automatically selected high-detail crops per pair
+- [`comparison_sheets/differences/`](comparison_sheets/differences/) — BF16-relative absolute-difference maps with a shared per-pair scale
+
+Difference heatmaps show divergence, not necessarily defects: even a small early numerical shift can produce a coherent but compositionally different eight-step result.
+
+## Prompt corpus
+
+### p01_portrait — portrait_microdetail
+
+Ultra-realistic close-up editorial portrait of an elderly woman by a north-facing window, natural unretouched skin with visible pores and fine wrinkles, individual silver-gray hairs and eyelashes, wet catchlights in both eyes, a dark indigo wool coat with clearly visible fabric weave, soft neutral background bokeh, restrained color grading, high micro-contrast only on the face.
+
+### p02_hands_group — anatomy_occlusion_counting
+
+Candid documentary photograph of exactly four adult friends seated around a small round wooden table, each person exchanging a different small object with another person, all eight hands fully visible, natural overlapping arms and fingers, ceramic cups and folded paper on the table, warm side lighting, realistic anatomy, medium-wide composition.
+
+### p03_package_text — product_typography
+
+Front-facing studio product photograph of a premium matte white beverage carton on a pale gray seamless background. The package has only three lines of crisp black printed text: ‘NORTHSTAR LAB’, ‘SERIES 08’, and ‘250 ml’. Add a thin cobalt-blue geometric border, a small silver cap, straight edges, subtle paper texture, and a soft contact shadow.
+
+OCR targets: NORTHSTAR LAB, SERIES 08, 250 ML.
+
+### p04_storefront_text — environment_typography_lowlight
+
+Rainy nighttime street photograph of a small corner cafe, viewed straight on through wet air and reflections. Three clearly readable signs say ‘OPEN 24 HOURS’, ‘CAFE LUMEN’, and ‘7TH STREET’. Deep blue shadows, warm amber windows, red neon reflections on asphalt, fine rain streaks, realistic perspective and restrained cinematic contrast.
+
+OCR targets: OPEN 24 HOURS, CAFE LUMEN, 7TH STREET.
+
+### p05_architecture — geometry_repetition
+
+Perfectly symmetrical photograph of a contemporary museum interior in strict one-point perspective, long rows of repeating concrete columns, hair-thin black railings, large glass panels, precisely aligned pale stone floor tiles, a distant centered doorway, diffuse skylight, clean straight verticals, fine architectural detail from foreground to background.
+
+### p06_reflections — specular_transparency
+
+Luxury studio still life of a polished chrome mechanical wristwatch beside a transparent rectangular perfume bottle on glossy black glass, tiny engraved numerals and gear details, controlled white strip reflections, realistic glass refraction and caustics, faint condensation, crisp edges, black background with smooth tonal falloff.
+
+### p07_foliage_bird — high_frequency_natural
+
+Backlit wildlife photograph of a small kingfisher perched among dense wet foliage, individually resolved blue and orange feathers, leaf veins, tiny droplets, thin crossing branches and spider silk, layered depth separation, soft forest background, natural green color variation, sharp subject without oversharpening.
+
+### p08_fog_neon — gradients_lowlight
+
+Empty foggy city street before dawn in monochromatic navy and cobalt blue, one distant magenta neon tube glowing through mist, extremely smooth sky and fog gradients, subtle shadow transitions, faint wet pavement reflections, preserved near-black detail, no crushed blacks, no visible banding, quiet minimalist composition.
+
+### p09_material_macro — material_texture
+
+Museum-style macro material study arranged as five adjacent samples: coarse woven natural linen, brushed stainless steel, cracked celadon ceramic glaze, porous wet black stone, and translucent handmade paper. Raking side light reveals microtexture while every material remains clearly distinct and neutrally colored.
+
+### p10_vector_gradient — flat_graphics_banding
+
+Minimalist Swiss-style vector poster with a warm ivory background, three perfectly aligned ultramarine circles, hair-thin black geometric construction lines, one large coral rectangle, and a perfectly smooth pale-yellow to orange gradient band. Precise spacing, clean flat fills, razor-sharp edges, no texture and no shadows.
+
+### p11_retro_anime — line_art_stylized
+
+Single frame from a refined 1980s retro-anime film: a young mechanic adjusting a tiny radio with both hands, expressive face, thin confident ink outlines, intricate patterned jacket, limited teal cream and burgundy palette, cel shading, detailed fingers and radio controls, clean line intersections, subtle analog film grain.
+
+### p12_watercolor — soft_stylized_gradients
+
+Delicate transparent watercolor landscape on cold-pressed cotton paper, pale dawn sky fading from cool gray-blue to warm peach, mist drifting between layered hills, translucent washes, granulating pigment, soft wet edges, sparse fine tree silhouettes and untouched white paper highlights.
+
+### p13_food — commercial_complex_scene
+
+High-end commercial food photograph of handmade mushroom ravioli in glossy brown butter sauce, visible steam, tiny sage leaves, grated cheese, crumbs and pepper, a transparent water glass, polished fork and folded linen, warm window light, shallow depth of field, appetizing natural color and detailed highlights.
+
+### p14_spatial_counts — spatial_reasoning_counting
+
+Surreal gallery installation containing exactly three red cubes beneath a clear glass arch, exactly two blue spheres behind the arch, and exactly one yellow cone in front, all six objects reflected in a shallow sheet of water, centered wide composition, neutral white room, physically consistent shadows and reflections.
+
+### p15_scientific_poster — diagram_labels
+
+Clean scientific cutaway poster of a compact greenhouse system on a white background, precise pipes, roots, vents and sunlight paths, four simple arrows with clearly readable uppercase labels ‘AIR’, ‘WATER’, ‘ROOTS’, and ‘LIGHT’, restrained green and blue palette, thin technical linework, balanced educational infographic layout.
+
+OCR targets: AIR, WATER, ROOTS, LIGHT.
+
+## Reproduction
+
+```powershell
+.\run_benchmark.ps1 preflight
+.\run_benchmark.ps1 weights
+.\run_benchmark.ps1 generate
+.\run_benchmark.ps1 analyze
+.\run_benchmark.ps1 sheets
+.\run_benchmark.ps1 report
+```
+
+The runner resumes only complete captures and rejects an existing result directory when the configuration hash differs. It never silently retries with different image settings.
+The external capture sampler was also compared against ComfyUI's built-in KSampler on the INT8 checkpoint: final latent and decoded float image were bit-identical with zero maximum absolute error. Evidence is in `validation/sampler_equivalence.json`.
+
+## Limitations
+
+1. The corpus contains 30 paired prompt-seed observations per format, optimized for artifact sensitivity rather than broad population-level aesthetic preference.
+2. BF16 is the original-checkpoint fidelity reference, not an external ground truth for semantic correctness.
+3. Pixel metrics become conservative when quantization changes composition rather than producing a local defect.
+4. No human preference test was requested; conclusions about aesthetics remain outside scope.
+5. FP8 and INT8 have accelerated Ada execution in this runtime. MXFP8 and NVFP4 do not, so only their storage and quality results are portable from this system.
+
+## Primary sources
+
+- [Krea 2 Turbo model card and official inference settings](https://huggingface.co/krea/Krea-2-Turbo)
+- [Comfy-Org Krea 2 repackaged checkpoints](https://huggingface.co/Comfy-Org/Krea-2)
+- [LPIPS paper](https://arxiv.org/abs/1801.03924)
+- [DISTS paper](https://arxiv.org/abs/2004.07728)
+- [DINOv2 paper](https://arxiv.org/abs/2304.07193)
+- [HPS v2 paper](https://arxiv.org/abs/2306.09341)
+- [MUSIQ paper](https://arxiv.org/abs/2108.05997)
+- [MANIQA paper](https://arxiv.org/abs/2204.08958)
+- [TOPIQ paper](https://arxiv.org/abs/2308.03060)
+
+## Raw artifact index
+
+- `manifest.json`: environment, dependency versions, checkpoint metadata, and hashes
+- `run_matrix.json`: all 150 preregistered scored runs
+- `runs.jsonl`: execution ledger including failures and timings
+- `captures/`: float decoded images, final latents, trajectories, PNGs, and per-run metadata
+- `metrics/`: all raw, summary, and inferential CSV/JSON tables
+- `telemetry/`: 100 ms GPU and system telemetry
+- `advanced_metric_cache/`: resumable per-model metric outputs

comparison_sheets/complete.json

@@ -0,0 +1,4 @@
+{
+  "complete": true,
+  "groups": 30
+}