Added V1.5<ul><li>Merged with the latest Krea 2 SNOFS v1.5</li></ul><hr />A merged of Krea 2 with the <a target="_blank" rel="ugc" href="https://civarchive.com/models/2761113/krea-2-identity-edit?modelVersionId=3139172">Krea 2 Identity Edit lora v1.2</a> adaptation by <a target="_blank" rel="ugc" href="https://huggingface.co/conradlocke/krea2-identity-edit">conradlocke</a> and <a target="_blank" rel="ugc" href="https://civarchive.com/models/1972981/snofs-sex-nudes-other-fun-stuff?modelVersionId=3290120">SNOFS v1.4 </a>LOKR by <a target="_blank" rel="ugc" href="https://civarchive.com/user/Ashen3">Ashen [</a><a target="_blank" rel="ugc" href="https://huggingface.co/Ashen3/SNOFS">Huggingface] </a>Both baked directly into the model so the separate loras are not required.Requires the <a target="_blank" rel="ugc" href="https://github.com/lbouaraba/comfyui-krea2edit">ComfyUI-Krea2Edit</a> node pack, the edit lora is trained with dual conditioning (in-context VAE tokens + image-grounded Qwen3-VL encoding) that stock nodes don't provide. Example Workflow is attached on the Optional File.Change the GGUF loader node to Load Diffusion Model node if you are using BF16, Int8 or Int4 model.GGUF loader : <a target="_blank" rel="ugc" href="https://github.com/molbal/ComfyUI-GGUF">https://github.com/molbal/ComfyUI-GGUF</a>All example images were created using the Q4_0 / Q4_KM GGUF variant at 0.7 MP resolution with a 3:4 aspect ratio. The BF16, Int8_convrot, int4_convrot variants haven’t been tested extensively, so please share your results here.<img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/87bd7c6e-18ea-410a-a3eb-746ab0b4ac71/original=true/87bd7c6e-18ea-410a-a3eb-746ab0b4ac71.jpeg" /><img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/684aa455-8708-4c00-b3ae-ea2985525a72/original=true/684aa455-8708-4c00-b3ae-ea2985525a72.jpeg" /><img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/9e58c393-8108-4600-849b-7e58f0f6e029/original=true/9e58c393-8108-4600-849b-7e58f0f6e029.jpeg" /><h3 id="precision-variants">Precision variants</h3>Several precision variants are available to let you choose the best balance between quality, VRAM usage, and performance:<ul><li>BF16 —&gt; The highest quality, highest precision, high VRAM usage.</li><li>INT8 ConvRot —&gt; Higher precision with lower quantization loss. Requires more VRAM than the INT4 variant.</li><li>Q6_K GGUF —&gt; Higher-quality 6-bit quantization, Mostly identical to Q8 with lower vram usage.</li><li>Q5_1 GGUF —&gt; High-quality 5-bit quantization with a good balance between quality and VRAM usage.</li><li>Q4_0 GGUF / Q4_KM —&gt; More aggressive 4-bit quantization with lower VRAM usage while retaining good image quality (The best balance for low vram user).</li><li>INT4 ConvRot —&gt; The most aggressive option, designed for lower VRAM usage and faster inference on supported hardware. Quality is slightly below the Q4 GGUF variants (The fastest).</li></ul>In general, expect the precision trade off to be approximately:BF16 &gt; INT8 ConvRot &gt; Q6_K &gt; Q5_1 &gt; Q4_KM &gt; Q4_0 &gt; INT4 ConvRotHigher precision generally provides better quality, while lower precision reduces VRAM requirements.<h2 id="credits">Credits</h2><ul><li>Krea 2 -&gt; Original base model by <a target="_blank" rel="ugc" href="https://www.krea.ai/">Krea AI</a></li><li>Krea 2 Identity Edit -&gt; Adaptation by <a target="_blank" rel="ugc" href="https://huggingface.co/conradlocke/krea2-identity-edit">conradlocke</a></li><li>SNOFS -&gt; by <a target="_blank" rel="ugc" href="https://civarchive.com/user/Ashen3">Ashen [</a><a target="_blank" rel="ugc" href="https://huggingface.co/Ashen3/SNOFS">Huggingface]</a></li></ul>This is an unofficial community modification and is not affiliated with or endorsed by <a target="_blank" rel="ugc" href="http://Krea.ai">Krea.ai</a>.

KREA 2 Edit SNOFS Merge

krea2EditSNOFSMerge_v15_int8.safetensors

krea2EditSNOFSMerge_v15.json

krea2EditSNOFSMerge_v15_bf16.safetensors

Files with SHA256: 2f5ff1ee860def3eb1ea45e0faefd535f4e4cefa2ca1c9bb720dd46c43e7d0a1