Model reference · open weights

Krea-2-Raw

Image krea Text→image 2 builds Its own licence terms 76k dl/mo

Krea-2-Raw is an open-weight image model from krea. Krea-2-Raw (BF16) weighs 35.7 GB; the smallest configuration that runs it is L40S 48 GB.

  • Krea-2-Raw is a 12.8B parameter text-to-image diffusion model developed by Krea.
  • It is intended as a base checkpoint for finetuning or post-training rather than direct inference.
  • The model supports English prompts and is released under the Krea 2 Community License.

Summary of the krea/Krea-2-Raw model card, 2026-10-01

What it is

Released bykrea
Released2026-06-18
Parameters12.8B
VRAM35.7 GB for the weights

What it runs on

Memory and cards for Krea-2-Raw (BF16)

35.7 GBweights, file size
26.3 GBbiggest part
5.0 GBworking memory, one 1024² image
537 MBruntime overhead
CardOne imageMemory
RTX 3060 12 GB … RTX 5090 32 GBdoes not fit
L40S 48 GBtight44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

Builds

Sizes, precisions & builds

BuildParamsPrecisionWeightsSmallest setup
Krea-2-Raw (above) ↗ 12.8BBF16 35.7 GBL40S 48 GB
Krea-2-Turbo ↗
packaged by unsloth
12.8BBF16 35.7 GBL40S 48 GB

From the model card

What krea says about Krea-2-Raw

Read the model card

Ungated mirror of krea/krea-2-turbo, republished by Unsloth so it can be downloaded without a Hub gate. The weights are unmodified. See NOTICE and LICENSE in this repo for the terms, which are the upstream terms and are unchanged.

Krea 2 Text-to-Image Model

Inference with the official codebase

  1. Setup the official Krea 2 codebase
  2. Download turbo.safetensors in this repo
  3. export OSS_TURBO= Run inference:
    uv run inference.py "a fox walking in the snow" \
     --checkpoint oss_turbo --steps 8 --cfg 0.0 --mu 1.15 --width 2048 --height 2048
    

Inference with diffusers

Install diffusers from source (for Krea2Pipeline):

pip install git+https://github.com/huggingface/diffusers.git
import torch
from diffusers import Krea2Pipeline

pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Turbo", torch_dtype=torch.bfloat16).to("cuda")
image = pipe("a fox in the snow", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("krea2.png")

Inference with SGLang

Install SGLang from source (https://github.com/sgl-project/sglang)

From the CLI:

sglang generate --model-path krea/Krea-2-Turbo \
    --prompt "a red fox sitting in fresh snow, golden hour, photorealistic" \
    --num-inference-steps 8 --height 1024 --width 1024 --save-output

See the full SGLang Krea 2 Cookbook here

Model Overview

  • Model Name: Krea 2
  • Version: v1.0
  • Release Date: June 22, 2026
  • Model Type: Text-to-image diffusion model
  • Architecture: Diffusion Transformer with 12 billion parameters
  • License: Krea 2 Community License
  • Release Format: Open-weight release and Krea-hosted product integrations
  • Model Developer: Krea.ai, Inc.

Model Family and Release Checkpoints

This model card covers the Krea 2 model family, including the following release checkpoints:

  • Krea 2 Raw: Base release checkpoint, prior to additional post-training and fine-tuning.
  • Krea 2 Turbo: Post-trained release checkpoint with additional fine-tuning and distillation.

Capabilities and Intended use

Krea 2 is a text-to-image diffusion model that generates images from natural-language text descriptions. The model is designed to support creative, commercial, developer, and research use cases, including image generation, concepting, design exploration, visual production workflows, and integration into applications and creative tools.

Out-of-Scope Uses

This model is not intended or designed for uses that violate applicable law or regulations, infringe or misappropriate third-party rights, generate or facilitate unlawful or harmful content (including CSAM, NCII, harassment or defamation), or support fully automated decision-making that adversely affects legal rights of individuals. This summary is non-exhaustive. Use of Krea 2 is subject to the Krea 2 Community License Agreement and must comply with the Acceptable Use Policy. In the event of any conflict, the Krea Acceptable Use Policy and Krea 2 Community License control.

Training Data

This model was developed using a combination of publicly available data, data licensed from third-party providers, and synthetic data generated through proprietary methods. The training data includes images and their associated captions or text descriptions.

Prior to training, data was filtered to remove certain categories of harmful content and reduce low-quality, duplicative, or irrelevant data. Krea also used curated and synthetic training data selected to improve prompt following, visual quality, and alignment with intended use cases.

Safety Measures

We implemented safety measures across the full model development lifecycle. We applied targeted fine-tuning techniques to reduce the model's susceptibility to generating harmful content in response to both direct and adversarial prompts, and we conducted multiple rounds of internal and external safety evaluation before release.

For Krea's hosted products incorporating Krea 2, we deploy input and output classifiers using a combination of proprietary and third-party detection tools to flag or block policy-violating prompts and generated images.

Because this is also an open-weights release, Krea does not control downstream deployment of the model. Under the Krea 2 Community License, deployers are required to implement content filtering measures or equivalent review processes to prevent the generation or distribution of unlawful or policy-violating content appropriate to their use case. Deployers who fail to implement required safeguards are in breach of the license. See the license for details.

We conducted multiple rounds of internal and external safety evaluations before release, including adversarial testing designed to assess the model's resilience to attempts to elicit harmful or policy-violating outputs. Testing covered sexually explicit content, non-consensual intimate imagery, child-safety risks, and other high-risk content categories. Based on these evaluations, the release checkpoints demonstrated high resilience against violative inputs across the tested risk categories.

Krea maintains reporting channels for harmful, illegal, or policy-violating outputs at safety@krea.ai. Reports involving potential CSAM are escalated to NCMEC as required by law. Krea reserves the right to update model weights or revoke access in response to identified misuse patterns.

Risks and Limitations

Krea 2 is a new technology and there are risks associated with its use. Testing conducted to date has not covered, nor could it cover, all possible scenarios. The model's potential outputs cannot be predicted in advance and may, in some instances, produce inaccurate, objectionable, or otherwise undesirable outputs.

This model is not intended to provide factual information. The model may fail to gene

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

Running it yourself

Run it on a rented GPU

Rent a machine by the hour. How to run this model is on its model card.

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