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Wan 2.2 I2V A14B on 12 GB of VRAM

Not at full quality. The 16-bit and 8-bit files are too big for 12 GB; the largest that fits is Q3_K_M (7.2 GB). The image-to-video Wan 2.2, and the most downloaded Wan 2.2 GGUF. Same two-model setup as the text-to-video version.

Video model · 14BAny 12 GB GPUData 2026-10-01
Tight
Only just.

Q3_K_M (7.2 GB) fits with only 0.5 GB to spare (about 11.5 GB of 12 GB). Quality: noticeable loss of detail. For better quality, Q4_K_M (9.7 GB) also runs, with about 2.0 GB spilling into system RAM - a little slower, still practical.

Best fileQ3_K_M
File size7.2 GB
VRAM needed~11.5 GB
System RAM32 GB+
Memory map · 12 GB GPU11.5 GB / 12 GB
06 GB12 GB
Weights Q3_K_M · 7.2 GBWorking memory · 3.5 GBReserve · 0.8 GBFree · 0.5 GB

Also try the FP8 file (14.3 GB) on NVIDIA GPUs. It does not fit entirely, but a current ComfyUI streams the overflow from RAM and native 8-bit files often beat a small GGUF that does fit. 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 (14.3 GB) on 12 GB, start with blocks_to_swap ≈ 20 (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 →

02Every file, on 12 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
28.6 GB32.9 GB20.9 GB too bigthe original weightsHugging Face →
Q8_0
GGUF · QuantStack
15.4 GB19.7 GB7.7 GB too bigpractically identical to the originalHugging Face →
FP8
SAFETENSORS · Comfy-Org
14.3 GB18.6 GB6.6 GB too bigpractically identical to the originalHugging Face →
Q6_K
GGUF · QuantStack
12.0 GB16.3 GB4.3 GB too bigvery close to the originalHugging Face →
Q5_K_M
GGUF · QuantStack
10.8 GB15.1 GB3.1 GB too bigclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · QuantStack
9.7 GB14.0 GBspills 2.0 GBgood; some loss in fine detail and textHugging Face →
Q3_K_M ←
GGUF · QuantStack
7.2 GB11.5 GBfits · 0.5 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · QuantStack
5.3 GB9.6 GBfits · 2.4 GB spareheavy loss; a last resortHugging 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.

03What to download

PartFileFolderSize
ModelWan2.2-I2V-A14B-HighNoise-Q3_K_M.gguf
high-noise model (early steps)
Q3_K_M · QuantStack/Wan2.2-I2V-A14B-GGUF
models/unet7.2 GBDownload →
ModelWan2.2-I2V-A14B-LowNoise-Q3_K_M.gguf
low-noise model (late steps)
Q3_K_M · QuantStack/Wan2.2-I2V-A14B-GGUF
models/unet7.2 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_2.2_ComfyUI_Repackaged
models/vae0.3 GBDownload →
Total download · keep about the same free on disk21.3 GB

Alternatives: UMT5-XXL FP16 (11.4 GB). Sizes from Hugging Face, 2026-10-01.