Can the Apple M2 Pro (32 GB) run OmniGen2?

73 pts

Yes, it runs well

Runs well. At FP16 it needs about 18.0 GB of 21.4 GB usable, with an estimated speed of 3.3 min.

Best precision: FP16
Memory mode: Everything on GPU
Time per image: 3.3 min
Output: 1024×1024, 50 steps

Download OmniGen2

Original weights · Hugging Face

Full-precision files from BAAI (VectorSpaceLab), for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/OmniGen2/OmniGen2 (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from BAAI (VectorSpaceLab). The weights themselves download from Hugging Face.

github.com/VectorSpaceLab/OmniGen2 (opens in a new tab)

git clone https://github.com/VectorSpaceLab/OmniGen2

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

How the A grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	29.7 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	3.4 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	15.0 / 15
Total	73.1 / 100	73 ptsGreat (A) · 73 of 100 points: Model quality 29.7/45, Memory fit 25.0/25, Speed 3.4/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every precision on the Apple M2 Pro (32 GB)

Precision	Memory needed	Available	Time per output	Memory mode	Fit	Grade · points	Download
`FP16`	18.0 GB	21.4 GB	3.3 min	Everything on GPU	Runs well	73 ptsGreat (A) · 73 of 100 points: Model quality 29.7/45, Memory fit 25.0/25, Speed 3.4/15, Memory use 15.0/15	Original weights (opens in a new tab)
`FP8`	10.3 GB	21.4 GB	3.0 min	Everything on GPU	Runs well	68 ptsGood (B) · 68 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 3.6/15, Memory use 11.1/15	Original weights (opens in a new tab)

Other hardware that runs it

79 ptsGreat (A) · 79 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 10.9/15, Memory use 14.9/15 AMD Radeon RX 9070 XT FP8 · 19 s
79 ptsGreat (A) · 79 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 10.8/15, Memory use 14.9/15 NVIDIA GeForce RTX 5080 FP8 · 19 s
79 ptsGreat (A) · 79 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 10.5/15, Memory use 14.9/15 NVIDIA GeForce RTX 4080 SUPER FP8 · 20 s
78 ptsGreat (A) · 78 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 9.9/15, Memory use 14.9/15 NVIDIA GeForce RTX 4070 Ti SUPER FP8 · 23 s
78 ptsGreat (A) · 78 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 9.9/15, Memory use 14.9/15 NVIDIA GeForce RTX 5070 Ti FP8 · 23 s
78 ptsGreat (A) · 78 of 100 points: Model quality 29.7/45, Memory fit 25.0/25, Speed 8.6/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 FP16 · 30 s

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.