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Can the Mac 48 GB run Wan Animate 2 (14B)?

Yes, but only just: 16-bit leaves 2.1 GB free on the Mac 48 GB.

Video model · 14B48 GB unified · ~40.2 GB for the GPU · 273–614 GB/s · Apple SiliconData 2026-10-01
Runs well
Yes.

Take 16-bit (32.8 GB). In use it comes to about 38.1 GB, with 2.1 GB left over on 40.2 GB.

Best file16-bit
File size32.8 GB
GPU memory needed~38.1 GB
Shared memory46 / 48 GB
Memory map · Mac 48 GB38.1 GB / 40.2 GB
020 GB40 GB
Weights 16-bit · 32.8 GBWorking memory · 4.5 GBReserve · 0.8 GBFree · 2.1 GB

01What to download

PartFileFolderSize
Modelwan_animate_2_bf16.safetensors
16-bit · Comfy-Org/Wan-Animate-2
models/diffusion_models32.8 GBDownload →
Text encoderumt5-xxl-encoder-Q8_0.gguf
UMT5-XXL GGUF Q8_0 · city96/umt5-xxl-encoder-gguf
models/text_encoders6.0 GBDownload →
VAEWan2_1_VAE_bf16.safetensors
Wan 2.1 VAE BF16 (Kijai) · Comfy-Org/Wan-Animate-2
models/vae0.3 GBDownload →
Also neededclip_vision_h.safetensors
CLIP Vision H · Comfy-Org/Wan-Animate-2
models/clip_vision1.3 GBDownload →
Total download · keep about the same free on disk40.4 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 46.4 GB of your 48 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 Animate 2 file on 40.2 GB

FileSizeNeededOn this cardQualityDownload
16-bit ←
SAFETENSORS · Comfy-Org
32.8 GB38.1 GBfits · 2.1 GB sparethe original weightsHugging Face →
Q8_0
GGUF · realrebelai
18.1 GB23.4 GBfits · 16.8 GB sparepractically identical to the originalHugging Face →
Q6_K
GGUF · realrebelai
14.2 GB19.5 GBfits · 20.7 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · realrebelai
12.7 GB18.0 GBfits · 22.2 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · realrebelai
11.3 GB16.6 GBfits · 23.6 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · realrebelai
8.6 GB13.9 GBfits · 26.3 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · realrebelai
6.5 GB11.8 GBfits · 28.4 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 4.5 GB of working memory for Wan Animate 2 and a 0.8 GB reserve. Sizes 2026-10-01. 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 Animate 2 on a Mac 48 GB, send your time per image and peak VRAM and it will appear here, credited.

04About the Mac 48 GB

A Mac with 48 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 40.2 GB of it by default (older macOS versions: about 38.7 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 48 GB: M3 Max, M4 Pro, M4 Max, M5 Pro, M5 Max (memory bandwidth 273–614 GB/s - the higher, the faster). Everything about Macs and local AI →

48 GB unified · ~40.2 GB for the GPU · 273–614 GB/s · Apple Silicon. Everything that runs on it →

05Questions

How much VRAM does Wan Animate 2 need?

Around 11.8 GB with the smallest file (Q2_K) and 22.0 GB with an 8-bit file (INT8). The full 16-bit file needs about 38.1 GB.

Which Wan Animate 2 file should I download for the Mac 48 GB?

16-bit (32.8 GB) from Comfy-Org/Wan-Animate-2.

How much do I need to download for Wan Animate 2 on the Mac 48 GB?

40.4 GB: wan_animate_2_bf16.safetensors, umt5-xxl-encoder-Q8_0.gguf, Wan2_1_VAE_bf16.safetensors, clip_vision_h.safetensors.