Model reference · open weights

Krea-2-Raw

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

Krea-2-Raw is an open-weight image model from Jinstudio. 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 byJinstudio
TypeImage models
TaskText→image
Parameters (lead)12.8B
Runs withdiffusers
Released2026-06-24
Popularity1k downloads / month
LicenceCommercial licence needed

About

What Krea-2-Raw is

This is the Krea 2 Raw checkpoint, its not recommended for inference use. Its a good base for finetuning or post-training for your own needs and domains. For example, one use-case is to train LoRAs on midtrain and directly use them on Krea 2 Turbo. See our collection of in-house trained LoRAs trained on Raw and meant to be used with Turbo: Krea-2 LoRA Collection

Read the full model card

Inference with the official codebase

  1. Setup the official Krea 2 codebase
  2. Download raw.safetensors in this repo
  3. export OSS_RAW= Run inference:
    uv run inference.py "a fox walking in the snow" \
     --checkpoint oss_raw --steps 52 --cfg 3.5 --width 1024 --height 1024
    

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-Raw", torch_dtype=torch.bfloat16).to("cuda")
image = pipe("a fox in the snow", num_inference_steps=52, guidance_scale=3.5).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-Raw \
    --prompt "a red fox sitting in fresh snow, golden hour, photorealistic" \
    --num-inference-steps 52 --height 1024 --width 1024 --guidance-scale 3.5 --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 oth

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

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys jinstudio-krea-2-raw for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (jinstudio-krea-2-raw 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":"jinstudio-krea-2-raw","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.

© 2026 AxForge · EU-hosted AI infrastructure Pricing Docs Trust Privacy Terms