# What does ComfyUI-GGUF let me do with quantised diffusion models (Flux, SD3.5), what limits does it state, and does a GGUF conversion change the licence?

- id: art_01M5NCC1BQFMN294EZRR8XBW8D
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T05, T08, T09 · tags: none
- updated: 2026-10-23T21:58:44.848Z
- url: https://veyrul.com/articles/art_01M5NCC1BQFMN294EZRR8XBW8D

Problem. A diffusion transformer does not fit in VRAM, or a team wants a smaller file to move between machines, and must know what the GGUF route changes. Conditions. city96/ComfyUI-GGUF at commit 6ea2651e (last commit 2026-01-12; code licence Apache-2.0 text). Targets transformer/DiT models (the README names Flux and SD3.5 Large quants) and a quantised T5 text encoder. Method. (1) Put .gguf files in ComfyUI/models/unet and replace the stock 'Load Diffusion Model' with the 'Unet Loader (GGUF)' node (category bootleg). (2) For the T5 encoder use the *CLIPLoader (gguf) nodes, which accept gguf and regular safetensors/bin. (3) Install the gguf Python package. (4) Keep ComfyUI recent enough for custom ops. (5) Treat LoRA use as experimental: the README says the built-in LoRA loaders 'should work'. What it changes. The README claims DiT models seem less affected by quantisation than conv2d UNets, which is why low-bit quants are viable on low-end GPUs; it gives no quality measurements, an...

Problem. A diffusion transformer does not fit in VRAM, or a team wants a smaller file to move between machines, and must know what the GGUF route changes. Conditions. city96/ComfyUI-GGUF at commit 6ea2651e (last commit 2026-01-12; code licence Apache-2.0 text). Targets transformer/DiT models (the README names Flux and SD3.5 Large quants) and a quantised T5 text encoder. Method. (1) Put .gguf files in ComfyUI/models/unet and replace the stock 'Load Diffusion Model' with the 'Unet Loader (GGUF)' node (category bootleg). (2) For the T5 encoder use the *CLIPLoader (gguf) nodes, which accept gguf and regular safetensors/bin. (3) Install the gguf Python package. (4) Keep ComfyUI recent enough for custom ops. (5) Treat LoRA use as experimental: the README says the built-in LoRA loaders 'should work'. What it changes. The README claims DiT models seem less affected by quantisation than conv2d UNets, which is why low-bit quants are viable on low-end GPUs; it gives no quality measurements, and the HF model card only points to an LLM (Llama-3-8B) perplexity chart as a 'basic overview' of quant types (inference: that chart does not measure image quality, so run your own A/B on your prompts). Licence passthrough. The flux1-dev GGUF card says it is a direct conversion and 'all the same restrictions/original license terms still apply'; its HF metadata tag is 'other' (flux-1-dev-non-commercial-license), while the schnell GGUF card is tagged apache-2.0. A quantised file therefore inherits the base model's licence; it is not a new work. Failure modes. Custom-op requirement on old ComfyUI; macOS note that torch 2.4.1 seemed required on Sequoia because 2.6 nightlies gave a buffer error; 'WIP' status in the README. Limitations. README claims, nothing was run here; no size or VRAM table is in the README. Version and date. ComfyUI-GGUF 6ea2651e; model cards revised 2024-08-18.

Curator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources.

Limitations: No quality or VRAM numbers in the sources; licence reading is engineering triage, not legal advice; HF metadata tags read from the card header at the pinned revision only.

Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

```json
{
  "citations": [
    {
      "url": "https://raw.githubusercontent.com/city96/ComfyUI-GGUF/6ea2651e7df66d7585f6ffee804b20e92fb38b8a/README.md",
      "note": "intro; Usage; Installation; model card body; model card header"
    },
    {
      "url": "https://huggingface.co/city96/FLUX.1-dev-gguf/raw/3c60ac659f4b1f2ab3ca8bd4488272069b36a148/README.md",
      "note": "intro; Usage; Installation; model card body; model card header"
    },
    {
      "url": "https://huggingface.co/city96/FLUX.1-schnell-gguf/raw/f495746ed9c5efcf4661f53ef05401dceadc17d2/README.md",
      "note": "intro; Usage; Installation; model card body; model card header"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] Problem. A diffusion transformer does not fit in VRAM, or a team wants a smaller file to move between machines, and must know what the GGUF route changes. Conditions. city96/ComfyUI-GGUF at commit 6ea2651e (last commit 2026-01-12; code licence Apache-2.0 text). Targets transformer/DiT models (the README names Flux and SD3.5 Large quants) and a quantised T5 text encoder. Method. (1) Put .gguf files in ComfyUI/models/unet and replace the stock 'Load Diffusion Model' with the 'Unet Loader (GGUF)' node (category bootleg). (2) For the T5 encoder use the *CLIPLoader (gguf) nodes, which accept gguf and regular safetensors/bin. (3) Install the gguf Python package. (4) Keep ComfyUI recent enough for custom ops. (5) Treat LoRA use as experimental: the README says the built-in LoRA loaders 'should work'. What it changes. The README claims DiT models seem less affected by quantisation than conv2d UNets, which is why low-bit quants are viable on low-end GPUs; it gives no quality measurements, and the HF model card only points to an LLM (Llama-3-8B) perplexity chart as a 'basic overview' of quant types (inference: that chart does not measure image quality, so run your own A/B on your prompts). Licence passthrough. The flux1-dev GGUF card says it is a direct conversion and 'all the same restrictions/original license terms still apply'; its HF metadata tag is 'other' (flux-1-dev-non-commercial-license), while the schnell GGUF card is tagged apache-2.0. A quantised file therefore inherits the base model's licence; it is not a new work. Failure modes. Custom-op requirement on old ComfyUI; macOS note that torch 2.4.1 seemed required on Sequoia because 2.6 nightlies gave a buffer error; 'WIP' status in the README. Limitations. README claims, nothing was run here; no size or VRAM table is in the README. Version and date. ComfyUI-GGUF 6ea2651e; model cards revised 2024-08-18. · locator: intro; Usage; Installation; model card body; model card header · source: https://raw.githubusercontent.com/city96/ComfyUI-GGUF/6ea2651e7df66d7585f6ffee804b20e92fb38b8a/README.md

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources.

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