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Can the Apple M3 Ultra (256 GB) run Wan 2.2 Animate 14B?

70 ptsGood (B) · 70 of 100 points: Model quality 35.1/45, Memory fit 25.0/25, Speed 2.2/15, Memory use 7.8/15

Yes, it runs well

Runs well. At FP16 it needs about 65.2 GB of 192 GB usable, with an estimated speed of 2.2 h.

Best precision
FP16
Memory mode
Everything on GPU
Time per clip
2.2 h
Output
1280×720, 77 frames, 40 steps

Download Wan 2.2 Animate 14B

Quantized files · GGUF for ComfyUI

Smaller GGUF versions for ComfyUI (with the ComfyUI-GGUF node). No sign-in needed; the model’s license still applies.

huggingface.co/QuantStack/Wan2.2-Animate-14B-GGUF (opens in a new tab)

Original weights · Hugging Face

Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/Wan-AI/Wan2.2-Animate-14B (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Alibaba. The weights themselves download from Hugging Face.

github.com/Wan-Video/Wan2.2 (opens in a new tab)

git clone https://github.com/Wan-Video/Wan2.2

Links checked 5 days ago against Hugging Face, Ollama and GitHub.

How the B 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.35.1 / 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.2.2 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.7.8 / 15
Total70.2 / 10070 ptsGood (B) · 70 of 100 points: Model quality 35.1/45, Memory fit 25.0/25, Speed 2.2/15, Memory use 7.8/15

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

Every precision on the Apple M3 Ultra (256 GB)

Precision Memory needed Available Time per output Memory mode Fit Grade · points Download
FP16 65.2 GB 192 GB 2.2 h Everything on GPU Runs well 70 ptsGood (B) · 70 of 100 points: Model quality 35.1/45, Memory fit 25.0/25, Speed 2.2/15, Memory use 7.8/15 Original weights (opens in a new tab)
FP8 41.5 GB 192 GB 2.0 h Everything on GPU Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 34.4/45, Memory fit 25.0/25, Speed 2.4/15, Memory use 5.0/15 Original weights (opens in a new tab)
Q8 GGUF 42.7 GB 192 GB 2.6 h Everything on GPU Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 2.1/15, Memory use 5.1/15 GGUF (opens in a new tab)
Q4 GGUF 34.6 GB 192 GB 2.7 h Everything on GPU Runs well 63 ptsGood (B) · 63 of 100 points: Model quality 32.6/45, Memory fit 25.0/25, Speed 2.0/15, Memory use 4.2/15 GGUF (opens in a new tab)

Other hardware that runs it

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.