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    "# How to use (Flux.2 Dev GGUF v2.0.1)\n\n**What it does:** text to image with Flux.2 Dev, GGUF-quantised for low VRAM. One pass: prompt, sample, decode, save.\n\n**Inputs (on the FLUX.2 dev (GGUF) node):**\n- **Prompt:** describe what you want to see. Positive wording works best (cfg is 1, there is no negative prompt).\n- **Seed:** randomize by default. Set the seed control to fixed to repeat an image.\n- **Steps:** 30. 20 works, 30+ gives a better result.\n- **CFG:** 1. Keep it at 1. Prompt strength is set by Flux Guidance (4) inside the node.\n- **Width / Height:** 1088 x 1920 (portrait). See the Recommendation note for sizes per aspect ratio.\n\n**Inside the node (double-click to open):**\n- Model loaders: GGUF model, Mistral text encoder (type flux2), Flux.2 VAE. Pick your own quant file in the GGUF loader.\n- Sampler: KSamplerAdvanced, uni_pc / normal.\n- The Sage attention patch node is set to disabled. Leave it, or use the launch flag below.\n\n**Tips:**\n- Out of memory: use a smaller GGUF quant or a smaller size (1.0 MP sizes in the Recommendation note).\n- Output goes to ComfyUI/output with the prefix ComfyUI.\n- Faster attention: start ComfyUI with --use-sage-attention (less VRAM). --use-ck-attention changes the image for the same seed.\n\n**Tested on:** no test hardware recorded for this workflow. ComfyUI 0.45.3: converts and validates (not run).\n"
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    "Downloads (same as downloads.md)\n\nEasiest: python scripts/frizzy.py doctor flux/flux2-dev (from the repo root; downloads missing models, installs the nodes).\n\nComfyUI/models/\n  diffusion_models/  flux2-dev-Q5_K_M.gguf\n      https://huggingface.co/city96/FLUX.2-dev-gguf (pick your quant)\n  text_encoders/     mistral_3_small_flux2_fp4_mixed.safetensors (12.3 GB)\n      https://huggingface.co/Comfy-Org/flux2-dev/tree/main/split_files/text_encoders\n  vae/               flux2-vae.safetensors (0.3 GB)\n      https://huggingface.co/Comfy-Org/flux2-dev/tree/main/split_files/vae\n\nSubfolders inside a model folder are fine. Pick the file again in the loader if the name differs.\n\nCustom node packs: ComfyUI-GGUF (city96), ComfyUI-KJNodes (kijai).\n"
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    "text": "Required models for Flux.2 D GGUF Workflow:\n\nFlux.2 Dev GGUF Model: https://huggingface.co/city96/FLUX.2-dev-gguf/tree/main\nText Encoder: https://huggingface.co/Comfy-Org/flux2-dev/tree/main/split_files/text_encoders\nVAE: https://huggingface.co/Comfy-Org/flux2-dev/tree/main/split_files/vae\n\nIf you need FP8 FLUX.2 D Version - https://huggingface.co/Comfy-Org/flux2-dev/tree/main/split_files/diffusion_models\nIf you need Text Encoder in GGUF - https://huggingface.co/unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF/tree/main\nFile save location\n\nComfyUI/\n├───📂 models/\n│   ├───📂 diffusion_models/\n│   │   ├─── flux2-dev-Q8_0.gguf\n│   ├───📂 loras/\n│   │   ├─── Any loras if you want (only for Flux.2 D, not Flux.1 D)\n│   ├───📂 text_encoders/\n│   │   └─── mistral_3_small_flux2_bf16.safetensors (or fp8 if you have low vram)\n│   └───📂 vae/\n│       └── flux2-vae.safetensors\n\n\nSageAttention.whl - https://github.com/woct0rdho/SageAttention/releases/tag/v2.2.0-windows. To install sageattention, u can .whl change to .zip and:\n1. If u don't have sageattention, just put folders from .zip to ComfyUI\\python_embeded\\Lib\\site-packages\n2. If u have older version sageattention, delete folders with sageattention in ComfyUI\\python_embeded\\Lib\\site-packages and put new folders from .zip\n\nTo install Triton (if u don't have Triton) go to ComfyUI\\python_embeded and install by command [pip install triton] via cmd\n\nif you got error BaseLoaderKJ._patch_modules.<locals>.attention_sage() got an unexpected keyword argument 'transformer_options', use run_nvidia_gpu - sageattention.bat instead run_nvidia_gpu.bat in ComfyUI from .zip archive\n\n\n\n"
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    "Recomend Resolutions:\n\n2.0 MP\n\n1:1 exact 1448 x 1448, rounded 1408 x 1408\n\n3:2 exact 1773 x 1182, rounded 1728 x 1152\n\n4:3 exact 1672 x 1254, rounded 1664 x 1216\n\n16:9 exact 1936 x 1089, rounded 1920 x 1088\n\n21:9 exact 2212 x 948, rounded 2176 x 960\n\n----------------------------\n\n1.0 MP \n\nI ended up with familiar numbers I've used with SDXL, which gives me confidence in the calculations.\n\n1:1 exact 1024 x 1024\n\n3:2 exact 1254 x 836, rounded 1216 x 832\n\n4:3 exact 1182 x 887, rounded 1152 x 896\n\n16:9 exact 1365 x 768, rounded 1344 x 768\n\n21:9 exact 1564 x 670, rounded 1536 x 640\n\n----------------------\n\n4.0 MP\n\n1:1 exact 2000 x 2000, rounded 2048 x 2048\n\n3:2 exact 2449 x 1663, rounded 2432 x 1620\n\n4:3 exact 2309 x 1732, rounded 2304 x 1728\n\n16:9 exact 2670 x 1502, rounded 2688 x 1512\n\n21:9 exact 3501 x 1308, rounded 3040 x 1304\n\nset from 20 to 30+ steps to generate image (30+ steps gives a better image result)\n\nAlso u can generate image UP TO 4K resolution (3840x2160)\n"
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    "text": "Adjust MultiGPU virtual vram from 8 to 32 gb, i recomend having 32 gb RAM at least\n\nRecomend Resolutions:\n\n2.0 MP\n\n1:1 exact 1448 x 1448, rounded 1408 x 1408\n\n3:2 exact 1773 x 1182, rounded 1728 x 1152\n\n4:3 exact 1672 x 1254, rounded 1664 x 1216\n\n16:9 exact 1936 x 1089, rounded 1920 x 1088\n\n21:9 exact 2212 x 948, rounded 2176 x 960\n\n----------------------------\n\n1.0 MP \n\nI ended up with familiar numbers I've used with SDXL, which gives me confidence in the calculations.\n\n1:1 exact 1024 x 1024\n\n3:2 exact 1254 x 836, rounded 1216 x 832\n\n4:3 exact 1182 x 887, rounded 1152 x 896\n\n16:9 exact 1365 x 768, rounded 1344 x 768\n\n21:9 exact 1564 x 670, rounded 1536 x 640\n\n----------------------\n\n4.0 MP\n\n1:1 exact 2000 x 2000, rounded 2048 x 2048\n\n3:2 exact 2449 x 1663, rounded 2432 x 1620\n\n4:3 exact 2309 x 1732, rounded 2304 x 1728\n\n16:9 exact 2670 x 1502, rounded 2688 x 1512\n\n21:9 exact 3501 x 1308, rounded 3040 x 1304\n\nset from 20 to 30+ steps to generate image (30+ steps gives a better image result)\n\nAlso u can generate image UP TO 4K resolution (3840x2160)\n"
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