Datasheet for local AI49 models98 GPUsData read 2026-09-25
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Wan 2.1 I2V 14B 480P on 20 GB of VRAM

Video model · 16.4BAny 20 GB GPUData 2026-09-25
Runs
Yes, with a compressed file.

Download Q6_K (14.2 GB). With the model's working memory it needs about 18.5 GB, leaving 1.5 GB spare on 20 GB. Quality: very close to the original. For better quality, FP8 (16.4 GB) also runs, with about 0.7 GB spilling into system RAM — a little slower, still practical.

Best fileQ6_K
File size14.2 GB
VRAM needed~18.5 GB
System RAM32 GB+
Memory map · 20 GB GPU18.5 GB / 20 GB
010 GB20 GB
Weights Q6_K · 14.2 GBWorking memory · 3.5 GBReserve · 0.8 GBFree · 1.5 GB
calculated from real file sizes plus working memory. Not yet measured on this setup. How this works.

Worth trying on NVIDIA GPUs: with an up-to-date ComfyUI, Dynamic VRAM (on by default for NVIDIA since March 2026) streams whatever does not fit from system RAM, and ComfyUI's own start-up message recommends native FP8/INT8 files over GGUF, saying they “will be faster even if they are larger than your memory”. So before settling for a heavily compressed GGUF, try the native FP8 file (16.4 GB). The file recommended above is the best one that fits entirely — the safe choice on older ComfyUI versions, AMD and Intel. Comfy blog: Dynamic VRAM →

Using Kijai's WanVideoWrapper instead of the native nodes? Its WanVideo BlockSwap node keeps part of the model in system RAM. To run the FP8 file (16.4 GB) on 20 GB, start with blocks_to_swap ≈ 3 (of 40). Each block is about 0.4 GB; raise the number if you still run out of memory, lower it for speed. estimate WanVideoWrapper →

01What to download

PartFileFolderSize
Modelwan2.1-i2v-14b-480p-Q6_K.gguf
Q6_K · city96/Wan2.1-I2V-14B-480P-gguf
models/unet14.2 GBDownload →
Text encoderumt5_xxl_fp8_e4m3fn_scaled.safetensors
UMT5-XXL FP8 (scaled) · Comfy-Org/Wan_2.1_ComfyUI_repackaged
models/text_encoders6.7 GBDownload →
VAEwan_2.1_vae.safetensors
Wan 2.1 VAE · Comfy-Org/Wan_2.1_ComfyUI_repackaged
models/vae0.3 GBDownload →
Also neededclip_vision_h.safetensors
CLIP Vision H · Comfy-Org/Wan_2.1_ComfyUI_repackaged
models/clip_vision1.3 GBDownload →
Total download · keep about the same free on disk22.5 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. 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.

System RAM: 32 GB or more. ComfyUI keeps the model file, the text encoder and the VAE in system RAM and moves them to the GPU as needed. With this set of files that is about 22.5 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 28.5 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated

02Every file, on 20 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
32.8 GB37.1 GB17.1 GB too bigthe original weightsHugging Face →
Q8_0
GGUF · city96
18.1 GB22.4 GB2.4 GB too bigpractically identical to the originalHugging Face →
FP8
SAFETENSORS · Comfy-Org
16.4 GB20.7 GBspills 0.7 GBpractically identical to the originalHugging Face →
Q6_K ←
GGUF · city96
14.2 GB18.5 GBfits · 1.5 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · city96
12.7 GB17.0 GBfits · 3.0 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · city96
11.3 GB15.6 GBfits · 4.4 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · city96
8.6 GB12.9 GBfits · 7.1 GB sparenoticeable loss of detailHugging Face →

Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 3.5 GB working memory for this model + 0.8 GB kept free for the system.

03The text encoder

UMT5-XXL + CLIP Vision H: 11.4 GB as 16-bit, 6.7 GB as FP8, 3.7 GB as GGUF Q4_K_M (plus CLIP Vision H (1.3 GB) for the input image). 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 20 GB the FP8 encoder fits on its own, so prompt encoding stays fast.