Can the Mac 16 GB run HiDream-O1-Image?
The smallest sensible file, 16-bit (16.4 GB), needs about 19.2 GB — 6.5 GB more than Mac 16 GB has. ComfyUI can still run it by streaming part of the model from system RAM. How much slower that is depends on your ComfyUI version, the file format and the PCIe link — see the note below.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Checkpoint | hidream_o1_image_bf16.safetensors 16-bit · Comfy-Org/HiDream-O1-Image | models/checkpoints | 16.4 GB | Download → |
| Total download · keep about the same free on disk | 16.4 GB | |||
One file: this model has no separate text encoder or 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 22.4 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 6.4 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 HiDream-O1 file on 12.7 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit ← SAFETENSORS · Comfy-Org | 16.4 GB | 19.2 GB | 6.5 GB too big | the original weights | Hugging 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. The Comfy-Org files are complete checkpoints (loaded from the checkpoints folder); there is no separate text encoder or VAE to add. No GGUF version was found. 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
This model has no separate text encoder: reading the prompt is built into the model itself, so its memory is already in the file sizes above.
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
With 20 GB you could run HiDream-O1 at 8-bit or better (16-bit, 16.4 GB) with no offloading.
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run HiDream-O1 on a Mac 16 GB, send your time per image and peak VRAM and it will appear here, credited.
07Questions
How much VRAM does HiDream-O1 need?
Around 10.9 GB with the smallest file (FP8) and 10.9 GB with an 8-bit file (FP8), counting working memory and a small system reserve. The full 16-bit file needs about 19.2 GB.
Which HiDream-O1 file should I download for the Mac 16 GB?
16-bit (16.4 GB) from Comfy-Org/HiDream-O1-Image.
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 HiDream-O1 on the Mac 16 GB?
About 16.4 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.