Wan 2.2 Animate 14B on Apple M2 Pro (32 GB)
Can the Apple M2 Pro (32 GB) run Wan 2.2 Animate 14B?
No, it doesn’t fit
No. Wan 2.2 Animate 14B needs about 21.3 GB even at Q4 GGUF; the Apple M2 Pro (32 GB) has 21.4 GB usable.
Download Wan 2.2 Animate 14B
Recommended: 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-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)
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/Wan2.2How the F grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 9.8 / 45 | |
|---|---|---|
| Memory fit | 0.0 / 25 | |
| Speed | 0.0 / 15 | |
| Memory use | 0.0 / 15 | |
| Total | 9.8 / 100 | 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 |
Every precision on the Apple M2 Pro (32 GB)
| Precision | Memory needed | Available | Time per output | Memory mode | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|---|
FP16 | 29.8 GB | 21.4 GB | — | — | Won't run | 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | Original weights (opens in a new tab) |
FP8 | 23.7 GB | 21.4 GB | — | — | Won't run | 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.3/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | Original weights (opens in a new tab) |
Q8 GGUF | 24.1 GB | 21.4 GB | — | — | Won't run | 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.4/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | GGUF (opens in a new tab) |
Q4 GGUF | 21.3 GB | 21.4 GB | — | — | Won't run | 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | GGUF (opens in a new tab) |
Hardware that can run it
- 80 ptsGreat (A) · 80 of 100 points: Model quality 35.1/45, Memory fit 25.0/25, Speed 5.4/15, Memory use 15.0/15 NVIDIA RTX PRO 6000 Blackwell
- 78 ptsGreat (A) · 78 of 100 points: Model quality 35.1/45, Memory fit 25.0/25, Speed 3.3/15, Memory use 15.0/15 AMD Ryzen AI Max+ 395 (128 GB)
- 77 ptsGreat (A) · 77 of 100 points: Model quality 35.1/45, Memory fit 25.0/25, Speed 1.9/15, Memory use 15.0/15 Apple M4 Max (128 GB)
- 76 ptsGreat (A) · 76 of 100 points: Model quality 35.1/45, Memory fit 25.0/25, Speed 3.2/15, Memory use 13.1/15 NVIDIA GB10 (128 GB)
- 74 ptsGreat (A) · 74 of 100 points: Model quality 34.7/45, Memory fit 23.0/25, Speed 1.8/15, Memory use 15.0/15 Apple M4 Max (64 GB)
- 74 ptsGreat (A) · 74 of 100 points: Model quality 34.7/45, Memory fit 23.0/25, Speed 1.4/15, Memory use 15.0/15 Apple M1 Max (64 GB)
Models that do run on the Apple M2 Pro (32 GB)
- 70 ptsGood (B) · 70 of 100 points: Model quality 22.1/45, Memory fit 25.0/25, Speed 12.1/15, Memory use 11.6/15 LTX-Video 2B
- 70 ptsGood (B) · 70 of 100 points: Model quality 31.0/45, Memory fit 23.0/25, Speed 1.7/15, Memory use 15.0/15 Wan 2.1 I2V 14B 480P
- 68 ptsGood (B) · 68 of 100 points: Model quality 24.3/45, Memory fit 25.0/25, Speed 4.5/15, Memory use 15.0/15 CogVideoX 5B
- 68 ptsGood (B) · 68 of 100 points: Model quality 24.3/45, Memory fit 25.0/25, Speed 4.5/15, Memory use 15.0/15 CogVideoX 5B I2V
- 68 ptsGood (B) · 68 of 100 points: Model quality 32.6/45, Memory fit 18.0/25, Speed 2.9/15, Memory use 15.0/15 FramePack I2V (HunyuanVideo 13B)
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.