Model reference · open weights

Krea2

Available as managed deployment Licence fee Image thfzjj · community Text→image 1 variants 826 dl/mo

Krea2 is an open-weight image model from thfzjj. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released bythfzjj
TypeImage models
TaskText→image
Runs withdiffusers
Released2026-08-02
Popularity826 downloads / month
LicenceCommercial licence needed

About

What Krea2 is

This repository provides an optimized FP8 (float8_e4m3fn) weight-only quantized version of the newly released Krea 2 OSS (Turbo) transformer.

This optimization reduces the model size from the original 24.76 GiB (BF16) down to 12.01 GiB, making it highly accessible and runnable on standard consumer hardware (such as 16GB and 24GB GPUs) without sacrificing output quality.

Read the full model card

⚠️ Licensing & Disclaimer

  • Original Model Creators: All credit goes to KREA.ai for the original research, architecture, and weights.
  • License: This model is subject to the KREA 2 License Agreement. Please read and comply with the official license terms before using these weights: KREA 2 Licensing Terms.
  • Purpose: This repository is a community-contributed utility. It does not claim ownership of the original model or architecture. Its sole purpose is to provide optimized, consumer-hardware-friendly weights for the open-source community.

🛠️ Quantization Details (Quality-First FP8)

Unlike generic global quantization scripts that aggressively convert every parameter (which often degrades generation details or introduces NaN/promotion calculation errors in neural networks), this model was quantized using a selective weight-only strategy:

  1. Targeted Quantization: Only 2D floating-point weight matrices (.weight keys with ndim >= 2 and element count > 1024) were quantized to torch.float8_e4m3fn.
  2. Preserved Precision:
    • All 1D vectors, biases, and normalization scales are kept in their native high-precision (float32 / bfloat16).
    • Highly sensitive projection/modulation layers (such as LastLayer.modulation.lin vectors) are completely preserved in high-precision. This prevents typical mathematical promotion bugs (such as BFloat16 and Float8 promotion issues in PyTorch) and retains original output fidelity.
  3. Weight Comparison:
    • Tensors Quantized to FP8: 266 tensors.
    • Tensors Kept in Native Precision: 166 tensors.
    • Size Reduction: 24.76 GiB ➔ 12.01 GiB (~51.5% VRAM / disk savings!).

🖼️ Sample Generations

Below are official sample outputs from the original Krea 2 OSS Turbo model (generated with the same BF16 weights this FP8 conversion is based on):

3DAnimeBeach
BlocksCelDog
FaceFlowersFox
FutureGoldfaceJester
MouseRedRide
SailorStatueTakeoff
TreeWind

🚀 How to Use in ComfyUI (Native — 0.25.0+)

ComfyUI 0.25.0+ has built-in Krea2 support. No custom nodes needed. Drop the workflow JSON into ComfyUI and drag it to the canvas.

1. Download Required Files

Place these in your ComfyUI/models/ folder:

FileFolderSource
krea2_turbo_fp8.safetensorsunet/AlperKTS/Krea2_FP8 ← You are here
qwen3vl_4b_fp8_scaled.safetensorstext_encoders/Comfy-Org/Qwen3-VL
qwen_image_vae.safetensorsvae/Comfy-Org/Qwen-Image_ComfyUI

2. Load the Workflow

Drag workflows/Krea 2 simple workflow.json onto your ComfyUI canvas.

3. Queue & Generate!

Turbo defaults: 8 steps, CFG 1.0, er_sde sampler, simple scheduler, 1280×720.


🤝 Acknowledgements

Special thanks to the KREA.ai team for releasing Krea 2 to the open-source community. For any commercial licensing inquiries or details about the model, please visit krea.ai.

From the published model card. Full card on the HuggingFace links in the sidebar.

How it works

How image models work

Text promptwhat to makeText encoderunderstands itDiffusion stepsdenoise to pixelsImagePNG / JPEGA diffusion model starts from noise and denoises it, guided by your prompt, into a finished image.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys thfzjj-krea2 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (thfzjj-krea2 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"thfzjj-krea2","prompt":"a red bicycle","size":"1024x1024"}'

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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