MODEL PROFILE

Krea-2-SVDQuant-ComfyUI

AlperKTS · Krea-2-SVDQuant-ComfyUI

Quantized **Krea 2** checkpoints for ComfyUI — about **2x faster** and **a third the size** of the usual FP8 version, with no calibration dataset needed, on both **Krea 2 Turbo** (distilled, 8 steps) and the **base** release. This repo holds the custom nodes, the All-in-One builder, and the `quantize_krea2.py` conversion script; the `.safetensors` files live on Hugging Face. Works on **any modern NVIDIA GPU** — INT8/W4A4 tensor cores go back to Turing (RTX 20-series). Benchmarked on an RTX 3090 (Ampere). Everything here was built from scratch against ComfyUI's own quantization backend and is 100% reproducible. > **Requires a cu130 (CUDA 13) or newer PyTorch build.** ComfyUI disables `comfy_kitchen`'s > CUDA backend on older torch builds, which silently drops every quantized checkpoint onto a > pure-Python fallback that is *slower than bf16*. If these checkpoints are slower than FP8 > for you, see TROUBLESHOOTING.md.

Image generationlicense:other
Context windowNot disclosed
Input → OutputText → Image
Model weightsNot verified
Profile updated2026/10/30 09:35:10
OVERVIEW

Model overview

Quantized **Krea 2** checkpoints for ComfyUI — about **2x faster** and **a third the size** of the usual FP8 version, with no calibration dataset needed, on both **Krea 2 Turbo** (distilled, 8 steps) and the **base** release. This repo holds the custom nodes, the All-in-One builder, and the `quantize_krea2.py` conversion script; the `.safetensors` files live on Hugging Face. Works on **any modern NVIDIA GPU** — INT8/W4A4 tensor cores go back to Turing (RTX 20-series). Benchmarked on an RTX 3090 (Ampere). Everything here was built from scratch against ComfyUI's own quantization backend and is 100% reproducible. > **Requires a cu130 (CUDA 13) or newer PyTorch build.** ComfyUI disables `comfy_kitchen`'s > CUDA backend on older torch builds, which silently drops every quantized checkpoint onto a > pure-Python fallback that is *slower than bf16*. If these checkpoints are slower than FP8 > for you, see TROUBLESHOOTING.md.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Sources & traceability

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