| --- |
| license: other |
| license_name: krea-2-community |
| license_link: https://www.krea.ai/krea-2-licensing |
| pipeline_tag: text-to-image |
| library_name: diffusers |
| tags: |
| - text-to-image |
| - image-generation |
| - diffusion |
| - flow-matching |
| - dit |
| - krea |
| base_model: krea/Krea-2-Raw |
| base_model_relation: finetune |
| --- |
| |
| # Krea 2 (K2) Base - Diffusers |
|
|
| Diffusers-format conversion of the Krea 2 **Base** checkpoint, the undistilled foundation |
| model of the Krea 2 family from [Krea](https://krea.ai). The Base checkpoint carries no step |
| or guidance distillation, which keeps it diverse and highly malleable. It is the checkpoint |
| intended for fine-tuning, post-training, and LoRA training. |
|
|
| LoRAs trained on Base apply cleanly to Krea 2 Turbo, so the recommended workflow is to train |
| on Base and run inference on [Krea-2-Turbo-Diffusers](https://huggingface.co/CalamitousFelicitousness/Krea-2-Turbo-Diffusers). |
|
|
| ## Model Summary |
|
|
| Krea 2 is a latent-diffusion image model trained from scratch with an emphasis on aesthetics |
| and stylistic control. The architecture is a single-stream multimodal diffusion transformer. |
|
|
| - **Transformer**: single-stream DiT, 12.9B parameters, 28 blocks at width 6144. Grouped-query |
| attention, a learned output gate, per-head QK normalization, and a 3-axis rotary embedding. |
| A text-fusion stage inside the transformer collapses twelve text-encoder hidden-state layers |
| into one conditioning stream. |
| - **Text encoder**: [Qwen/Qwen3-VL-4B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct), |
| tapped at twelve intermediate layers (text-only conditioning). |
| - **VAE**: the Qwen-Image autoencoder (`AutoencoderKLQwenImage`, f8, 16 latent channels). |
| - **Sampler**: flow matching with a resolution-aware timestep shift. |
|
|
| Weights are stored in their original mixed precision (bf16 matmuls, fp32 norms and modulations). |
|
|
| ## Recommended Settings |
|
|
| Base is undistilled and uses classifier-free guidance with a negative prompt. |
|
|
| | Setting | Value | |
| | ------- | ----- | |
| | Steps | 52 | |
| | Guidance (CFG) | 3.5 | |
| | Resolution | up to 1024 x 1024 | |
|
|
| The timestep shift is resolution-aware: the conditioning interpolates the shift between low and |
| high resolution, so no manual tuning is required across sizes. |
|
|
| ## Prompting |
|
|
| Natural-language prompts are recommended. Long, detailed descriptions yield the best results, |
| though strong images are produced from short prompts as well. For text rendering, the words to |
| be rendered are wrapped in quotes. An optional prompt-expansion system prompt is available in |
| the upstream [krea-2-oss](https://github.com/krea-ai) repository. |
|
|
| ## License |
|
|
| The weights are released under the [Krea 2 community license](https://www.krea.ai/krea-2-licensing). |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{krea2, |
| title = {Krea 2}, |
| author = {Krea}, |
| year = {2026}, |
| url = {https://www.krea.ai/krea-2} |
| } |
| ``` |
|
|
