Can the Mac 128 GB run Wan 2.2 I2V A14B?
Yes. 16-bit fits on the Mac 128 GB with 82.5 GB to spare.
16-bit (28.6 GB) needs about 32.9 GB in use, so 82.5 GB of the 115.4 GB stays free: room for a larger image, a LoRA or a ControlNet.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | wan2.2_i2v_high_noise_14B_fp16.safetensors high-noise model (early steps) 16-bit · Comfy-Org/Wan_2.2_ComfyUI_Repackaged | models/diffusion_models | 28.6 GB | Download → |
| Model | wan2.2_i2v_low_noise_14B_fp16.safetensors low-noise model (late steps) 16-bit · Comfy-Org/Wan_2.2_ComfyUI_Repackaged | models/diffusion_models | 28.6 GB | Download → |
| Text encoder | umt5-xxl-encoder-Q8_0.gguf UMT5-XXL GGUF Q8_0 · city96/umt5-xxl-encoder-gguf | models/text_encoders | 6.0 GB | Download → |
| VAE | wan_2.1_vae.safetensors Wan 2.1 VAE · Comfy-Org/Wan_2.2_ComfyUI_Repackaged | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 63.5 GB | |||
Alternatives: UMT5-XXL FP16 (11.4 GB). On a Mac, FP8 text encoders do not load, so a 16-bit one is listed - or a GGUF one, loaded with “CLIPLoader (GGUF)” from the ComfyUI-GGUF nodes. Sizes from Hugging Face, 2026-10-01.
Shared memory: about 69.5 GB of your 128 GB. On this machine the model, the text encoder, the VAE and the operating system all use the same memory. That leaves room, so nothing has to be swapped to disk. calculated
02Every Wan 2.2 I2V file on 115.4 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit ← SAFETENSORS · Comfy-Org | 28.6 GB | 32.9 GB | fits · 82.5 GB spare | the original weights | Hugging Face → |
| Q8_0 GGUF · QuantStack | 15.4 GB | 19.7 GB | fits · 95.7 GB spare | practically identical to the original | Hugging Face → |
| Q6_K GGUF · QuantStack | 12.0 GB | 16.3 GB | fits · 99.1 GB spare | very close to the original | Hugging Face → |
| Q5_K_M GGUF · QuantStack | 10.8 GB | 15.1 GB | fits · 100.3 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · QuantStack | 9.7 GB | 14.0 GB | fits · 101.4 GB spare | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · QuantStack | 7.2 GB | 11.5 GB | fits · 103.9 GB spare | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · QuantStack | 5.3 GB | 9.6 GB | fits · 105.8 GB spare | heavy loss; a last resort | Hugging Face → |
“Needed” adds 3.5 GB of working memory for Wan 2.2 I2V and a 0.8 GB reserve. Sizes 2026-10-01. Wan 2.2 A14B uses two files of this size (high-noise and low-noise); only one sits in VRAM at a time, both must fit in system RAM. 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.
03Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Wan 2.2 I2V on a Mac 128 GB, send your time per image and peak VRAM and it will appear here, credited.
04About the Mac 128 GB
A Mac with 128 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 115.4 GB of it by default (older macOS versions: about 103.1 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 128 GB: M1 Ultra, M2 Ultra, M3 Max, M4 Max, M5 Max (memory bandwidth 300–800 GB/s - the higher, the faster). Everything about Macs and local AI →
128 GB unified · ~115.4 GB for the GPU · 300–800 GB/s · Apple Silicon. Everything that runs on it →
05Questions
How much VRAM does Wan 2.2 I2V need?
Around 9.6 GB with the smallest file (Q2_K) and 18.6 GB with an 8-bit file (FP8). The full 16-bit file needs about 32.9 GB.
Which Wan 2.2 I2V file should I download for the Mac 128 GB?
16-bit (28.6 GB) from Comfy-Org/Wan_2.2_ComfyUI_Repackaged.
FP8 or Q8_0 for Wan 2.2 I2V on the Mac 128 GB?
Q8_0 (15.4 GB). The Mac 128 GB has no FP8 maths, so FP8 (14.3 GB) only saves memory and is a step further from the original.
How much do I need to download for Wan 2.2 I2V on the Mac 128 GB?
63.5 GB: wan2.2_i2v_high_noise_14B_fp16.safetensors, wan2.2_i2v_low_noise_14B_fp16.safetensors, umt5-xxl-encoder-Q8_0.gguf, wan_2.1_vae.safetensors.