Check my GPU →

Can the RTX 3060 Ti 8 GB run Wan 2.2 Animate 14B?

Not entirely. Even Q4_K_M is 8.8 GB over 8 GB, so ComfyUI keeps part of it in system RAM.

Video model · 17.3B8 GB GDDR6 · 256-bit · 448 GB/s · AmpereData 2026-10-01
Offload
Not entirely in VRAM, but it can still run.

The smallest sensible file, Q4_K_M (11.5 GB), needs about 16.8 GB - 8.8 GB more than RTX 3060 Ti 8 GB has. ComfyUI can still run it by streaming part of the model from system RAM. How much slower that is depends on your ComfyUI version, the file format and the PCIe link - see the note below.

Best fileQ4_K_M
File size11.5 GB
VRAM needed~16.8 GB
System RAM32 GB+
Memory map · RTX 3060 Ti 8 GB16.8 GB needed · 8.8 GB over 8 GB
08 GB17 GB
Weights Q4_K_M · 11.5 GBWorking memory · 4.5 GBReserve · 0.8 GBSpills to system RAM · 8.8 GB

Also try the FP8 file (17.3 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 →

01With more VRAM

With 24 GB you could run Wan 2.2 Animate at 8-bit or better (FP8, 17.3 GB) with no offloading: for example on the RTX 4090 24 GB, RTX 3090 24 GB, RX 7900 XTX 24 GB.

What changes from the RTX 3060 Ti 8 GB to the RTX 5060 Ti 16 GB →

02Every Wan 2.2 Animate file on 8 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
34.5 GB39.8 GB31.8 GB too bigthe original weightsHugging Face →
Q8_0
GGUF · QuantStack
18.7 GB24.0 GB16.0 GB too bigpractically identical to the originalHugging Face →
FP8
SAFETENSORS · Kijai
17.3 GB22.6 GB14.6 GB too bigpractically identical to the originalHugging Face →
INT8
SAFETENSORS · Comfy-Org
18.4 GB23.7 GB15.7 GB too bigpractically identical to the originalHugging Face →
Q6_K
GGUF · QuantStack
14.6 GB19.9 GB11.9 GB too bigvery close to the originalHugging Face →
Q5_K_M
GGUF · QuantStack
13.0 GB18.3 GB10.3 GB too bigclose; small differences in fine detailHugging Face →
Q4_K_M ←
GGUF · QuantStack
11.5 GB16.8 GB8.8 GB too biggood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · QuantStack
8.6 GB13.9 GB5.9 GB too bignoticeable loss of detailHugging Face →
Q2_K
GGUF · QuantStack
6.5 GB11.8 GB3.8 GB too bigheavy loss; a last resortHugging Face →

“Needed” adds 4.5 GB of working memory for Wan 2.2 Animate and a 0.8 GB reserve. Sizes 2026-10-01.

03What to download

PartFileFolderSize
ModelWan2.2-Animate-14B-Q4_K_M.gguf
Q4_K_M · QuantStack/Wan2.2-Animate-14B-GGUF
models/unet11.5 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 →
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 disk19.8 GB

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

04Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run Wan 2.2 Animate on a RTX 3060 Ti 8 GB, send your time per image and peak VRAM and it will appear here, credited.

05About the RTX 3060 Ti 8 GB

The RTX 3060 Ti 8 GB (Ampere) has no FP8 compute. FP8 files still load and save memory, but ComfyUI converts them back before the maths, so there is no speed gain - Q8_0 GGUF is the closer-to-original 8-bit choice. ComfyUI can compute INT8 files natively on NVIDIA, which is worth a try where a model offers one.

8 GB GDDR6 · 256-bit · 448 GB/s · Ampere. Everything that runs on it →

06Questions

How much VRAM does Wan 2.2 Animate need?

Around 11.8 GB with the smallest file (Q2_K) and 22.6 GB with an 8-bit file (FP8). The full 16-bit file needs about 39.8 GB.

Which Wan 2.2 Animate file should I download for the RTX 3060 Ti 8 GB?

Q4_K_M (11.5 GB) from QuantStack/Wan2.2-Animate-14B-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

FP8 or Q8_0 for Wan 2.2 Animate on the RTX 3060 Ti 8 GB?

Q8_0 (18.7 GB). The RTX 3060 Ti 8 GB has no FP8 maths, so FP8 (17.3 GB) only saves memory and is a step further from the original.

How much do I need to download for Wan 2.2 Animate on the RTX 3060 Ti 8 GB?

19.8 GB: Wan2.2-Animate-14B-Q4_K_M.gguf, umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors, clip_vision_h.safetensors.