Datasheet for local AI49 models98 GPUsData read 2026-09-25
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Can the Mac 32 GB run Qwen-Image?

Image model · 20B32 GB unified · ~26.8 GB for the GPU · 120–400 GB/s · Apple SiliconData 2026-09-25
Runs well
Yes — and comfortably.

Download Q8_0 (21.8 GB). With the model's working memory it needs about 24.6 GB, leaving 2.2 GB spare on 26.8 GB. Quality: practically identical to the original.

Best fileQ8_0
File size21.8 GB
GPU memory needed~24.6 GB
Shared memory45 / 32 GB
Memory map · Mac 32 GB24.6 GB / 26.8 GB
013 GB27 GB
Weights Q8_0 · 21.8 GBWorking memory · 2.0 GBReserve · 0.8 GBFree · 2.2 GB
calculated from real file sizes plus working memory. Not yet measured on this setup. How this works.

01What to download

PartFileFolderSize
Modelqwen-image-Q8_0.gguf
Q8_0 · city96/Qwen-Image-gguf
models/unet21.8 GBDownload →
Text encoderqwen_2.5_vl_7b.safetensors
Qwen2.5-VL 7B BF16 · Comfy-Org/Qwen-Image_ComfyUI
models/text_encoders16.6 GBDownload →
VAEqwen_image_vae.safetensors
Qwen-Image VAE · Comfy-Org/Qwen-Image_ComfyUI
models/vae0.3 GBDownload →
Total download · keep about the same free on disk38.6 GB

On a Mac, FP8 text encoders do not load, so a 16-bit one is listed. Sizes read from Hugging Face (2026-09-25). “Download” links start the file directly; the file name links are the same files the official ComfyUI workflows use.

Shared memory: about 44.6 GB of your 32 GB. On this machine the model, the text encoder, the VAE and the operating system all use the same memory. That is about 12.6 GB more than there is. It still runs: while the model works, the system compresses or swaps the idle text encoder, so loading and changing the prompt get slower. A smaller file or text encoder avoids that. calculated

02Every Qwen-Image file on 26.8 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
40.9 GB43.7 GB16.9 GB too bigthe original weightsHugging Face →
Q8_0 ←
GGUF · city96
21.8 GB24.6 GBfits · 2.2 GB sparepractically identical to the originalHugging Face →
Q6_K
GGUF · city96
16.8 GB19.6 GBfits · 7.2 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · city96
14.9 GB17.7 GBfits · 9.1 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · city96
13.1 GB15.9 GBfits · 10.9 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · city96
9.7 GB12.5 GBfits · 14.3 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · city96
7.1 GB9.9 GBfits · 16.9 GB spareheavy loss; a last resortHugging Face →

Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 2 GB working memory for this model + 0.8 GB kept free for the system. FP8 and INT8 files are left out on a Mac: Apple GPUs cannot compute FP8, so ComfyUI either fails to load them or converts them back to 16-bit, which saves no memory. Use a 16-bit or GGUF file.

03The text encoder

Qwen2.5-VL 7B: 16.6 GB as 16-bit, 9.4 GB as FP8. ComfyUI encodes the prompt first and can push the encoder out of VRAM before sampling, so it does not have to fit together with the model. On 26.8 GB the FP8 encoder fits on its own, so prompt encoding stays fast.

04About this GPU

A Mac with 32 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 26.8 GB of it by default (older macOS versions: about 22.9 GB); that is the figure used here. ComfyUI can go past it, but macOS then starts compressing and swapping memory and everything slows down. ComfyUI runs on Apple GPUs through PyTorch's MPS backend. 16-bit and GGUF files work; FP8 and INT8 files do not save memory on a Mac, so they are skipped. Speed is the catch: even the fastest Macs are several times slower per image than a desktop RTX card. Chips sold with 32 GB: M1 Pro, M1 Max, M2 Pro, M2 Max, M4, M5, M6 (memory bandwidth 120–400 GB/s — the higher, the faster). Everything about Macs and local AI →

Mac 32 GB: 32 GB unified · ~26.8 GB for the GPU · 120–400 GB/s · Apple Silicon. Everything that runs on the Mac 32 GB →

05What more VRAM would change

Nothing to gain for this model: the Mac 32 GB already runs a top-quality file entirely in VRAM. More memory would only help with bigger images, longer clips or several models at once.

06Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run Qwen-Image on a Mac 32 GB, send your time per image and peak VRAM and it will appear here, credited.

07Questions

How much VRAM does Qwen-Image need?

Around 9.9 GB with the smallest file (Q2_K) and 23.2 GB with an 8-bit file (FP8), counting working memory and a small system reserve. The full 16-bit file needs about 43.7 GB.

Which Qwen-Image file should I download for the Mac 32 GB?

Q8_0 (21.8 GB) from city96/Qwen-Image-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

Is FP8 faster than GGUF on the Mac 32 GB?

No. This GPU has no FP8 compute, so ComfyUI converts FP8 weights back before the maths. FP8 only saves memory here; Q8_0 GGUF is the closer-to-original 8-bit pick.

How much do I need to download for Qwen-Image on the Mac 32 GB?

About 38.6 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 26.8 GB card, 48 GB of system RAM or more is recommended.