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Can the Apple M2 Pro (32 GB) run Wan 2.2 S2V 14B (speech to video)?

68 ptsGood (B) · 68 of 100 points: Model quality 31.8/45, Memory fit 20.0/25, Speed 1.6/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q4 GGUF it needs about 15.6 GB of 21.4 GB usable, with an estimated speed of 4.3 h.

Best precision
Q4 GGUF
Memory mode
Text encoder offloaded
Time per clip
4.3 h
Output
832×480, 81 frames, 40 steps

Download Wan 2.2 S2V 14B (speech to video)

Recommended for the Apple M2 Pro (32 GB): q4_gguf. Every other precision has its own download link in the table below.

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.

Download the q4_gguf (Q4_K_S) file (opens in a new tab)

huggingface.co/QuantStack/Wan2.2-S2V-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-S2V-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 7 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.31.8 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.20.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.1.6 / 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
Total68.4 / 10068 ptsGood (B) · 68 of 100 points: Model quality 31.8/45, Memory fit 20.0/25, Speed 1.6/15, 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 17.0 GB 21.4 GB 4.5 h Sequential CPU offload Runs well 62 ptsGood (B) · 62 of 100 points: Model quality 34.2/45, Memory fit 12.0/25, Speed 1.6/15, Memory use 15.0/15 Original weights (opens in a new tab)
FP8 11.3 GB 21.4 GB 4.0 h Sequential CPU offload Runs well 59 ptsGood (B) · 59 of 100 points: Model quality 33.5/45, Memory fit 12.0/25, Speed 1.7/15, Memory use 12.2/15 Original weights (opens in a new tab)
Q8 GGUF 11.7 GB 21.4 GB 5.1 h Sequential CPU offload Runs well 59 ptsGood (B) · 59 of 100 points: Model quality 33.9/45, Memory fit 12.0/25, Speed 1.5/15, Memory use 12.6/15 GGUF (opens in a new tab)
Q4 GGUF 15.6 GB 21.4 GB 4.3 h Text encoder offloaded Runs well 68 ptsGood (B) · 68 of 100 points: Model quality 31.8/45, Memory fit 20.0/25, Speed 1.6/15, Memory use 15.0/15 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.