Files read on Hugging Face: 2026-10-24

FLUX.2 [dev] GGUF files and Mac RAM

32 billion parameter rectified flow transformer for text-to-image, editing and combining images, with a 24B Mistral Small text encoder. Model use is non-commercial; outputs may be used commercially within the license limits.

Black Forest Labs · Updated 2026-10-24
Answer

No published Mac run with a GGUF build yet. The smallest complete GGUF download is 34.75 GB; a download that fits in memory does not prove the model runs.

Smallest Mac with a published run
none yetunknown below
Smallest complete download
34.75 GBQ4_K_M GGUF
Files read
2026-10-24Hugging Face

FLUX Non-Commercial License. Commercial use: restricted. Excluded territories: none listed. Model use is non-commercial. Output may be used commercially except as expressly prohibited, and may not train, fine-tune or distill a competing FLUX model.

Table 1

Which exact GGUF files make a complete build?

Only builds with every required component and an exact probed file size are shown.

Q4_K_M GGUF

gguf · Q4_K_M · 34.75 GB complete

Mac routes: ComfyUI, stable-diffusion.cpp

Exact component files for Q4_K_M GGUF
FileComponentRequiredDownloadSource
flux2-dev-Q4_K_M.ggufcity96/FLUX.2-dev-ggufFLUX.2 transformerditYes20.08 GBHugging FaceRead 2026-10-24
Mistral-Small-3.2-24B-Instruct-2506-Q4_K_M.ggufunsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUFMistral Small 3.2 text encodertext_encoderYes14.33 GBHugging FaceRead 2026-10-24
ae.safetensorsblack-forest-labs/FLUX.2-devFLUX.2 VAEvaeYes0.34 GBHugging FaceRead 2026-10-24

Build sources: FLUX.2-dev GGUF card · stable-diffusion.cpp FLUX.2 guide.

Q8_0 GGUF

gguf · Q8_0 · 49.67 GB complete

Mac routes: ComfyUI, stable-diffusion.cpp

Exact component files for Q8_0 GGUF
FileComponentRequiredDownloadSource
flux2-dev-Q8_0.ggufcity96/FLUX.2-dev-ggufFLUX.2 transformerditYes35.00 GBHugging FaceRead 2026-10-24
Mistral-Small-3.2-24B-Instruct-2506-Q4_K_M.ggufunsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUFMistral Small 3.2 text encodertext_encoderYes14.33 GBHugging FaceRead 2026-10-24
ae.safetensorsblack-forest-labs/FLUX.2-devFLUX.2 VAEvaeYes0.34 GBHugging FaceRead 2026-10-24

Build sources: FLUX.2-dev GGUF card · stable-diffusion.cpp FLUX.2 guide.

Table 2

Does it fit your Mac's RAM?

Published names the exact measured machine. est. is a memory calculation. unknown means the run verdict is not established, not that the model fails.

Run verdicts by Mac memory tier
Mac RAMComplete buildDownloadRun verdictBasis
8 GBQ4_K_M GGUFQ4_K_M · ComfyUI34.75 GBDoes not fitest.
16 GBQ4_K_M GGUFQ4_K_M · ComfyUI34.75 GBDoes not fitest.
24 GBQ4_K_M GGUFQ4_K_M · ComfyUI34.75 GBDoes not fitest.
32 GBQ4_K_M GGUFQ4_K_M · ComfyUI34.75 GBDoes not fitest.
48 GBQ4_K_M GGUFQ4_K_M · ComfyUI34.75 GBunknownunknown
64 GBQ4_K_M GGUFQ4_K_M · ComfyUI34.75 GBunknownunknown
96 GBQ4_K_M GGUFQ4_K_M · ComfyUI34.75 GBunknownunknown
128 GBQ4_K_M GGUFQ4_K_M · ComfyUI34.75 GBunknownunknown

How does it rank in blind votes?

#38 of 82 in text to image blind votes, from 77,988 votes.

Quality: blind human votes from flux-2-dev (arena.ai), CC BY 4.0, snapshot 2026-10-07. Scores are for the Arena checkpoint, not your local quantized build.

Which Mac software routes are listed?

  • ComfyUI

    Official

    Formats: safetensors, gguf. Memory policy: component stages stay resident.

    On Apple Silicon ComfyUI runs on PyTorch MPS, not MLX. GGUF files need the separate city96/ComfyUI-GGUF custom node. Resident size is the sum of the weights, an upper bound: ComfyUI can unload models between stages and publishes no per-model Mac peak.

    Sources: ComfyUI README · ComfyUI system requirements · ComfyUI CLI arguments · ComfyUI-GGUF README

  • stable-diffusion.cpp

    Official

    Formats: gguf, safetensors. Memory policy: component stages stay resident.

    C/C++ runner with Metal on Mac and CUDA on NVIDIA. It reads GGUF and safetensors, and its docs keep a page per model family. Resident size is the sum of the weights, an upper bound.

    Sources: stable-diffusion.cpp README, backends

What does the official configuration say?

"Official deployment documentation says 24 to 32GB of VRAM can use 4-bit quantization. This is an NVIDIA statement, not a Mac minimum."

Source: FLUX.2 deployment guide · Read 2026-10-24.

What known issues should you check?

Sources