Datasheet for local AI49 models98 GPUsData read 2026-09-25
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Can the Mac 16 GB run Stable Diffusion 3.5 Large?

Image model · 8.1B16 GB unified · ~12.7 GB for the GPU · 68.25–200 GB/s · Apple SiliconData 2026-09-25
Runs well
Yes — and comfortably.

Download Q8_0 (8.8 GB). With the model's working memory it needs about 11.1 GB, leaving 1.6 GB spare on 12.7 GB. Quality: practically identical to the original.

Best fileQ8_0
File size8.8 GB
GPU memory needed~11.1 GB
Shared memory21 / 16 GB
Memory map · Mac 16 GB11.1 GB / 12.7 GB
06 GB13 GB
Weights Q8_0 · 8.8 GBWorking memory · 1.5 GBReserve · 0.8 GBFree · 1.6 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-Q8_0.gguf
Q8_0 · city96/stable-diffusion-3.5-large-gguf
models/unet8.8 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 disk15.5 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 21.5 GB of your 16 GB. On this machine the model, the text encoder, the VAE and the operating system all use the same memory. That is about 5.5 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 SD 3.5 Large file on 12.7 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · stabilityai
16.5 GB18.8 GB6.1 GB too bigthe original weightsHugging Face →
Q8_0 ←
GGUF · city96
8.8 GB11.1 GBfits · 1.6 GB sparepractically identical to the originalHugging Face →
Q5_1
GGUF · city96
6.3 GB8.6 GBfits · 4.1 GB spareclose; small differences in fine detailHugging Face →
Q4_1
GGUF · city96
5.3 GB7.6 GBfits · 5.1 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 12.7 GB the FP8 encoder fits on its own, so prompt encoding stays fast.

04About this GPU

A Mac with 16 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 12.7 GB of it by default (older macOS versions: about 11.5 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 16 GB: M1, M1 Pro, M2, M2 Pro, M3, M4, M5, M6 (memory bandwidth 68.25–200 GB/s — the higher, the faster). Everything about Macs and local AI →

Mac 16 GB: 16 GB unified · ~12.7 GB for the GPU · 68.25–200 GB/s · Apple Silicon. Everything that runs on the Mac 16 GB →

05What more VRAM would change

Nothing to gain for this model: the Mac 16 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 16 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 16 GB?

Q8_0 (8.8 GB) from city96/stable-diffusion-3.5-large-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

Is FP8 faster than GGUF on the Mac 16 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 16 GB?

About 15.5 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 12.7 GB card, 32 GB of system RAM or more is recommended.