Datasheet for local AI49 models98 GPUsData read 2026-09-25
No adsNo tracking
Check my GPU →

Can the Mac 16 GB run Wan 2.1 T2V 1.3B?

Video model · 1.3B16 GB unified · ~12.7 GB for the GPU · 68.25–200 GB/s · Apple SiliconData 2026-09-25
Runs well
Yes — and comfortably.

Download 16-bit (2.8 GB). With the model's working memory it needs about 5.6 GB, leaving 7.1 GB spare on 12.7 GB. Quality: the original weights.

Best file16-bit
File size2.8 GB
GPU memory needed~5.6 GB
Shared memory15 / 16 GB
Memory map · Mac 16 GB5.6 GB / 12.7 GB
06 GB13 GB
Weights 16-bit · 2.8 GBWorking memory · 2.0 GBReserve · 0.8 GBFree · 7.1 GB
calculated from real file sizes plus working memory. Not yet measured on this setup. How this works.

01What to download

PartFileFolderSize
Modelwan2.1_t2v_1.3B_fp16.safetensors
16-bit · Comfy-Org/Wan_2.1_ComfyUI_repackaged
models/diffusion_models2.8 GBDownload →
Text encoderumt5-xxl-encoder-Q8_0.gguf
UMT5-XXL GGUF Q8_0 · city96/umt5-xxl-encoder-gguf
models/text_encoders6.0 GBDownload →
VAEwan_2.1_vae.safetensors
Wan 2.1 VAE · Comfy-Org/Wan_2.1_ComfyUI_repackaged
models/vae0.3 GBDownload →
Total download · keep about the same free on disk9.1 GB

Alternatives: UMT5-XXL FP16 (11.4 GB). The 16-bit text encoder is a little more faithful; the smaller one is chosen here because it loads faster and needs less RAM. 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 read from Hugging Face (2026-09-25). “Download” links start the file directly; the file name links are the same files the official ComfyUI workflows use.

Shared memory: about 15.1 GB of your 16 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 2.1 1.3B file on 12.7 GB

FileSizeNeededOn this cardQualityDownload
16-bit ←
SAFETENSORS · Comfy-Org
2.8 GB5.6 GBfits · 7.1 GB sparethe original weightsHugging Face →
Q8_0
GGUF · samuelchristlie
1.5 GB4.3 GBfits · 8.4 GB sparepractically identical to the originalHugging Face →
Q6_K
GGUF · samuelchristlie
1.2 GB4.0 GBfits · 8.7 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · samuelchristlie
1.1 GB3.9 GBfits · 8.8 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · samuelchristlie
1.0 GB3.8 GBfits · 8.9 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · samuelchristlie
0.7 GB3.5 GBfits · 9.2 GB sparenoticeable loss of detailHugging Face →

Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 2 GB working memory for this model + 0.8 GB kept free for the system.

03The text encoder

UMT5-XXL: 11.4 GB as 16-bit, 6.7 GB as FP8, 3.7 GB as GGUF Q4_K_M. ComfyUI encodes the prompt first and can push the encoder out of VRAM before sampling, so it does not have to fit together with the model. On 12.7 GB the FP8 encoder fits on its own, so prompt encoding stays fast.

04About this GPU

A Mac with 16 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 12.7 GB of it by default (older macOS versions: about 11.5 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 16 GB: M1, M1 Pro, M2, M2 Pro, M3, M4, M5, M6 (memory bandwidth 68.25–200 GB/s — the higher, the faster). Everything about Macs and local AI →

Mac 16 GB: 16 GB unified · ~12.7 GB for the GPU · 68.25–200 GB/s · Apple Silicon. Everything that runs on the Mac 16 GB →

05What more VRAM would change

Nothing to gain for this model: the Mac 16 GB already runs a top-quality file entirely in VRAM. More memory would only help with bigger images, longer clips or several models at once.

06Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run Wan 2.1 1.3B on a Mac 16 GB, send your time per image and peak VRAM and it will appear here, credited.

07Questions

How much VRAM does Wan 2.1 1.3B need?

Around 3.5 GB with the smallest file (Q3_K_M) and 4.3 GB with an 8-bit file (Q8_0), counting working memory and a small system reserve. The full 16-bit file needs about 5.6 GB.

Which Wan 2.1 1.3B file should I download for the Mac 16 GB?

16-bit (2.8 GB) from Comfy-Org/Wan_2.1_ComfyUI_repackaged.

Is FP8 faster than GGUF on the Mac 16 GB?

No. This GPU has no FP8 compute, so ComfyUI converts FP8 weights back before the maths. FP8 only saves memory here; Q8_0 GGUF is the closer-to-original 8-bit pick.

How much do I need to download for Wan 2.1 1.3B on the Mac 16 GB?

About 9.1 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 12.7 GB card, 16 GB of system RAM or more is recommended.