Can the Mac 24 GB run Wan 2.1 T2V 14B?
Not at full quality. The 16-bit and 8-bit files are too big for the Mac 24 GB; the largest that fits is Q6_K (12.5 GB).
Take Q6_K (12.5 GB). In use it comes to about 16.8 GB, with 2.8 GB left over on 19.6 GB. Quality: very close to the original. For better quality, Q8_0 (15.9 GB) also runs, with about 0.6 GB spilling into system RAM - a little slower, still practical.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | wan2.1-t2v-14b-Q6_K.gguf Q6_K · city96/Wan2.1-T2V-14B-gguf | models/unet | 12.5 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_2.1_ComfyUI_repackaged | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 18.8 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 24.8 GB of your 24 GB. On this machine the model, the text encoder, the VAE and the operating system all use the same memory. That is about 0.8 GB more than there is. It still runs: while the model works, the system compresses or swaps the idle text encoder, so loading and changing the prompt get slower. A smaller file or text encoder avoids that. calculated
02Every Wan 2.1 14B file on 19.6 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 28.6 GB | 32.9 GB | 13.3 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · city96 | 15.9 GB | 20.2 GB | spills 0.6 GB | practically identical to the original | Hugging Face → |
| Q6_K ← GGUF · city96 | 12.5 GB | 16.8 GB | fits · 2.8 GB spare | very close to the original | Hugging Face → |
| Q5_K_M GGUF · city96 | 11.3 GB | 15.6 GB | fits · 4.0 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · city96 | 10.1 GB | 14.4 GB | fits · 5.2 GB spare | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · city96 | 7.6 GB | 11.9 GB | fits · 7.7 GB spare | noticeable loss of detail | Hugging Face → |
“Needed” adds 3.5 GB of working memory for Wan 2.1 14B 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 2.1 14B on a Mac 24 GB, send your time per image and peak VRAM and it will appear here, credited.
04With more VRAM
With 24 GB you could run Wan 2.1 14B at 8-bit or better (Q8_0, 15.9 GB) with no offloading: for example on the RTX 4090 24 GB, RTX 3090 24 GB, RX 7900 XTX 24 GB.
05About the Mac 24 GB
A Mac with 24 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 19.6 GB of it by default (older macOS versions: about 17.2 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 24 GB: M2, M3, M4, M4 Pro, M5, M5 Pro, M6 (memory bandwidth 100–307 GB/s - the higher, the faster). Everything about Macs and local AI →
24 GB unified · ~19.6 GB for the GPU · 100–307 GB/s · Apple Silicon. Everything that runs on it →
06Questions
How much VRAM does Wan 2.1 14B need?
Around 11.9 GB with the smallest file (Q3_K_M) and 18.6 GB with an 8-bit file (FP8). The full 16-bit file needs about 32.9 GB.
Which Wan 2.1 14B file should I download for the Mac 24 GB?
Q6_K (12.5 GB) from city96/Wan2.1-T2V-14B-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
FP8 or Q8_0 for Wan 2.1 14B on the Mac 24 GB?
Q8_0 (15.9 GB). The Mac 24 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 2.1 14B on the Mac 24 GB?
18.8 GB: wan2.1-t2v-14b-Q6_K.gguf, umt5-xxl-encoder-Q8_0.gguf, wan_2.1_vae.safetensors.