Can the Mac 24 GB run SDXL 1.0?
Download 16-bit (6.9 GB). With the model's working memory it needs about 7.1 GB, leaving 12.5 GB spare on 19.6 GB. Quality: the original weights.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Checkpoint | sd_xl_base_1.0.safetensors 16-bit · stabilityai/stable-diffusion-xl-base-1.0 | models/checkpoints | 6.9 GB | Download → |
| Total download · keep about the same free on disk | 6.9 GB | |||
One file: the checkpoint already contains the text encoders and the VAE. 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 12.9 GB of your 24 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 SDXL file on 19.6 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit ← SAFETENSORS · stabilityai | 6.9 GB | 7.1 GB | fits · 12.5 GB spare | the original weights | Hugging Face → |
Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 1.2 GB working memory for this model + 0.8 GB kept free for the system. The 6.94 GB checkpoint also holds the two text encoders and the VAE. During sampling only the UNet (about 5.1 GB at 16-bit, 2.6B parameters) has to sit in VRAM, so that is the figure used for the 16-bit file.
03The text encoder
The text encoder is inside the checkpoint, so there is nothing extra to download.
04About this GPU
A Mac with 24 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 19.6 GB of it by default (older macOS versions: about 17.2 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 24 GB: M2, M3, M4, M4 Pro, M5, M5 Pro, M6 (memory bandwidth 100–307 GB/s — the higher, the faster). Everything about Macs and local AI →
Mac 24 GB: 24 GB unified · ~19.6 GB for the GPU · 100–307 GB/s · Apple Silicon. Everything that runs on the Mac 24 GB →
05What more VRAM would change
Nothing to gain for this model: the Mac 24 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 SDXL on a Mac 24 GB, send your time per image and peak VRAM and it will appear here, credited.
07Questions
How much VRAM does SDXL need?
Around 7.1 GB with the smallest file (16-bit), counting working memory and a small system reserve.
Which SDXL file should I download for the Mac 24 GB?
16-bit (6.9 GB) from stabilityai/stable-diffusion-xl-base-1.0.
Is FP8 faster than GGUF on the Mac 24 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 SDXL on the Mac 24 GB?
About 6.9 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 19.6 GB card, 16 GB of system RAM or more is recommended.