Datasheet for local AI49 models98 GPUsData read 2026-09-25
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Can the Mac 32 GB run Stable Diffusion 3.5 Large?

Image model · 8.1B32 GB unified · ~26.8 GB for the GPU · 120–400 GB/s · Apple SiliconData 2026-09-25
Runs well
Yes — and comfortably.

Download 16-bit (16.5 GB). With the model's working memory it needs about 18.8 GB, leaving 8.0 GB spare on 26.8 GB. Quality: the original weights.

Best file16-bit
File size16.5 GB
GPU memory needed~18.8 GB
Shared memory29 / 32 GB
Memory map · Mac 32 GB18.8 GB / 26.8 GB
013 GB27 GB
Weights 16-bit · 16.5 GBWorking memory · 1.5 GBReserve · 0.8 GBFree · 8.0 GB
calculated from real file sizes plus working memory. Not yet measured on this setup. How this works.

01What to download

PartFileFolderSize
Modelsd3.5_large.safetensors
16-bit · stabilityai/stable-diffusion-3.5-large
models/diffusion_models16.5 GBDownload →
Text encodert5-v1_1-xxl-encoder-Q8_0.gguf
T5-XXL GGUF Q8_0 · city96/t5-v1_1-xxl-encoder-gguf
models/text_encoders5.1 GBDownload →
Text encoderclip_l.safetensors
CLIP-L · Comfy-Org/stable-diffusion-3.5-fp8
models/text_encoders0.2 GBDownload →
Text encoderclip_g.safetensors
CLIP-G · Comfy-Org/stable-diffusion-3.5-fp8
models/text_encoders1.4 GBDownload →
Total download · keep about the same free on disk23.2 GB

Alternatives: T5-XXL FP16 (9.8 GB). The 16-bit text encoder is a little more faithful; the smaller one is chosen here because it loads faster and needs less RAM. On a Mac, FP8 text encoders do not load, so a 16-bit one is listed — or a GGUF one, loaded with “CLIPLoader (GGUF)” from the ComfyUI-GGUF nodes. 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 29.2 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 leaves room, so nothing has to be swapped to disk. calculated

02Every SD 3.5 Large file on 26.8 GB

FileSizeNeededOn this cardQualityDownload
16-bit ←
SAFETENSORS · stabilityai
16.5 GB18.8 GBfits · 8.0 GB sparethe original weightsHugging Face →
Q8_0
GGUF · city96
8.8 GB11.1 GBfits · 15.7 GB sparepractically identical to the originalHugging Face →
Q5_1
GGUF · city96
6.3 GB8.6 GBfits · 18.2 GB spareclose; small differences in fine detailHugging Face →
Q4_1
GGUF · city96
5.3 GB7.6 GBfits · 19.2 GB sparegood; some loss in fine detail and textHugging Face →

Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 1.5 GB working memory for this model + 0.8 GB kept free for the system.

03The text encoder

CLIP-L + CLIP-G + T5-XXL: 9.8 GB as 16-bit, 4.9 GB as FP8 (T5-XXL sizes shown; CLIP-L and CLIP-G add about 1.6 GB). 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 SD 3.5 Large on a Mac 32 GB, send your time per image and peak VRAM and it will appear here, credited.

07Questions

How much VRAM does SD 3.5 Large need?

Around 7.6 GB with the smallest file (Q4_1) and 11.1 GB with an 8-bit file (Q8_0), counting working memory and a small system reserve. The full 16-bit file needs about 18.8 GB.

Which SD 3.5 Large file should I download for the Mac 32 GB?

16-bit (16.5 GB) from stabilityai/stable-diffusion-3.5-large.

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 SD 3.5 Large on the Mac 32 GB?

About 23.2 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, 32 GB of system RAM or more is recommended.