---
license: apache-2.0
base_model: krea/Krea-2-Turbo
tags:
- comfyui
- quantization
- int4
- w4a4
- convrot
- krea2
---

# Krea-2 Turbo — INT4 tensorwise W4A4 (+ConvRot, mixed int8 fallback)

**W4A4** quantization of [Krea-2 Turbo](https://huggingface.co/krea/Krea-2-Turbo)
(bf16 source: [Comfy-Org/Krea-2](https://huggingface.co/Comfy-Org/Krea-2)):
packed signed INT4 weights with group-256 regular-Hadamard **ConvRot** rotation
(arXiv [2512.03673](https://arxiv.org/abs/2512.03673)), activations rotated online
and dynamically quantized inside the kernel. Calibration-free.

Mixed recipe: 224 block Linears = **128 INT4 + 96 int8_tensorwise fallback**,
selected by measured per-layer sensitivity: each layer was swapped alone to
W4A4 on real sampling inputs, ranked by final-output drift, then chosen by
impact-per-byte at a fixed size budget (all `wv`/`wk`, 27/28 `wo`, the most
sensitive `mlp.down`/`gate`/`wq` layers). +0.95 dB over the class-heuristic
recipe at identical size and speed. The shared modulation projector `tproj`
and the text-fusion transformer stay bf16.

## Samples

![BF16 vs INT4 comparison](samples_krea2_turbo.jpg)

Same seed/prompt, BF16 top vs INT4-mixed bottom. Few-step turbo sampling amplifies trajectory divergence (composition shifts) while style, detail and lighting stay at parity — no quantization artifacts.

## ⚠️ Runtime requirement

Needs the `int4_tensorwise` runtime, which is **not in any released ComfyUI /
comfy-kitchen yet**. In-flight:
[comfy-kitchen PR #63](https://github.com/Comfy-Org/comfy-kitchen/pull/63)
(kernels + layout) and the
[ComfyUI loader branch](https://github.com/HK416-TYPED/ComfyUI/tree/feat/int4-tensorwise-loader)
— to try this checkpoint today, run that ComfyUI branch with the PR's
comfy-kitchen branch on `PYTHONPATH` (or installed). On a stock release it
fails with a clear "format not available" error.

## Measurements (NVIDIA L4 / SM 8.9, 1024x1024, 8 steps, cfg 1.0, 3 prompts)

| checkpoint | per image |
| --- | --- |
| **this model (int4 mixed)** | **18 s** |
| bf16 | 24 s |

Weights: **9.25 GB** vs 28 GB bf16 (−67%) — fits a 24 GB card with headroom where
bf16 needs weight streaming. PSNR vs bf16 (same seed): 17.7 dB (min 14.5) — few-step turbo models amplify trajectory divergence; visual inspection shows style/quality parity with composition shifts, no quantization artifacts.

## Reproduce

```bash
comfy-quants export-model-int4-tensorwise \
  --config configs/krea2_int4_tensorwise_mixed.yaml \
  --source krea2_turbo_bf16.safetensors \
  --out krea2_turbo_int4_tensorwise_mixed.safetensors
```

Produced by [comfy-quants](https://github.com/Comfy-Org/comfy-quants)
(branch `feat/int4-tensorwise`). Use with `text_encoders/qwen3vl_4b` +
`vae/qwen_image_vae` from Comfy-Org/Krea-2.