Check my GPU →

Can the RTX 5060 Ti 16 GB run Wan 2.2 I2V A14B?

Not at full quality. The 16-bit and 8-bit files are too big for the RTX 5060 Ti 16 GB; the largest that fits is Q5_K_M (10.8 GB).

Video model · 14B16 GB GDDR7 · 128-bit · 448 GB/s · BlackwellData 2026-10-01
Runs
Yes, with a compressed file.

Q5_K_M (10.8 GB) fits with only 0.9 GB to spare (about 15.1 GB of 16 GB). Quality: close; small differences in fine detail. For better quality, Q6_K (12.0 GB) also runs, with about 0.3 GB spilling into system RAM - a little slower, still practical.

Best fileQ5_K_M
File size10.8 GB
VRAM needed~15.1 GB
System RAM48 GB+
Memory map · RTX 5060 Ti 16 GB15.1 GB / 16 GB
08 GB16 GB
Weights Q5_K_M · 10.8 GBWorking memory · 3.5 GBReserve · 0.8 GBFree · 0.9 GB

Also try the FP8 file (14.3 GB) on this GPU. 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 RTX 5060 Ti 16 GB, start with blocks_to_swap ≈ 9 (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
ModelWan2.2-I2V-A14B-HighNoise-Q5_K_M.gguf
high-noise model (early steps)
Q5_K_M · QuantStack/Wan2.2-I2V-A14B-GGUF
models/unet10.8 GBDownload →
ModelWan2.2-I2V-A14B-LowNoise-Q5_K_M.gguf
low-noise model (late steps)
Q5_K_M · QuantStack/Wan2.2-I2V-A14B-GGUF
models/unet10.8 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 disk28.6 GB

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

System RAM: 48 GB or more. These files (both noise models) take about 28.6 GB of RAM while loaded, 34.6 GB with Windows and ComfyUI. What happens with less. calculated

02Every Wan 2.2 I2V file on 16 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
28.6 GB32.9 GB16.9 GB too bigthe original weightsHugging Face →
FP8
SAFETENSORS · Comfy-Org
14.3 GB18.6 GB2.6 GB too bigpractically identical to the originalHugging Face →
Q8_0
GGUF · QuantStack
15.4 GB19.7 GB3.7 GB too bigpractically identical to the originalHugging Face →
Q6_K
GGUF · QuantStack
12.0 GB16.3 GBspills 0.3 GBvery close to the originalHugging Face →
Q5_K_M ←
GGUF · QuantStack
10.8 GB15.1 GBfits · 0.9 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · QuantStack
9.7 GB14.0 GBfits · 2.0 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · QuantStack
7.2 GB11.5 GBfits · 4.5 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · QuantStack
5.3 GB9.6 GBfits · 6.4 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.

03Measured and reported results

LabelSetupResultPeak VRAMDateSource
reportedvideo_wan2_2_14B_i2v template (quant not stated) · 720p
“RTX5060ti 16GBだと165.9秒なので、2〜3倍時間が必要ですが、落ちずに720p動画が生成できる事はたいしたものです。”
Comparison figure given in the RTX 3060 post, presumably same 720p/53-frame test (not explicitly restated); steps not stated
165.9 s / clip (53 frames)—2025-11-26note.com →

Other people's numbers are copied as published, with a link. Send yours.

05Questions

How much VRAM does Wan 2.2 I2V need?

Around 9.6 GB with the smallest file (Q2_K) and 18.6 GB with an 8-bit file (FP8). The full 16-bit file needs about 32.9 GB.

Which Wan 2.2 I2V file should I download for the RTX 5060 Ti 16 GB?

Q5_K_M (10.8 GB) from QuantStack/Wan2.2-I2V-A14B-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

FP8 or Q8_0 for Wan 2.2 I2V on the RTX 5060 Ti 16 GB?

FP8 (14.3 GB): the RTX 5060 Ti 16 GB computes it natively, while Q8_0 (15.4 GB) is unpacked on the fly.

How much do I need to download for Wan 2.2 I2V on the RTX 5060 Ti 16 GB?

28.6 GB: Wan2.2-I2V-A14B-HighNoise-Q5_K_M.gguf, Wan2.2-I2V-A14B-LowNoise-Q5_K_M.gguf, umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors.