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Can the RTX 4090 24 GB run Wan 2.2 Animate 14B?

Yes, but only just: FP8 leaves 1.4 GB free on the RTX 4090 24 GB.

Video model · 17.3B24 GB GDDR6X · 384-bit · 1008 GB/s · Ada LovelaceData 2026-10-01
Runs well
Yes, just.

FP8 (17.3 GB) fits with only 1.4 GB to spare (about 22.6 GB of 24 GB).

Best fileFP8
File size17.3 GB
VRAM needed~22.6 GB
System RAM32 GB+
Memory map · RTX 4090 24 GB22.6 GB / 24 GB
012 GB24 GB
Weights FP8 · 17.3 GBWorking memory · 4.5 GBReserve · 0.8 GBFree · 1.4 GB

01What to download

PartFileFolderSize
ModelWan2_2-Animate-14B_fp8_scaled_e4m3fn_KJ_v2.safetensors
FP8 · Kijai/WanVideo_comfy_fp8_scaled
models/diffusion_models17.3 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 disk25.6 GB

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

02Every Wan 2.2 Animate file on 24 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
34.5 GB39.8 GB15.8 GB too bigthe original weightsHugging Face →
FP8 ←
SAFETENSORS · Kijai
17.3 GB22.6 GBfits · 1.4 GB sparepractically identical to the originalHugging Face →
INT8
SAFETENSORS · Comfy-Org
18.4 GB23.7 GBfits · 0.3 GB sparepractically identical to the originalHugging Face →
Q8_0
GGUF · QuantStack
18.7 GB24.0 GBspills 0.0 GBpractically identical to the originalHugging Face →
Q6_K
GGUF · QuantStack
14.6 GB19.9 GBfits · 4.1 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · QuantStack
13.0 GB18.3 GBfits · 5.7 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · QuantStack
11.5 GB16.8 GBfits · 7.2 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · QuantStack
8.6 GB13.9 GBfits · 10.1 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · QuantStack
6.5 GB11.8 GBfits · 12.2 GB spareheavy 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.

03Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run Wan 2.2 Animate on a RTX 4090 24 GB, send your time per image and peak VRAM and it will appear here, credited.

04About the RTX 4090 24 GB

The RTX 4090 24 GB is an Ada Lovelace GPU with hardware FP8, so ComfyUI can compute Comfy-Org's FP8 files natively: small and fast. (Plain FP8 files use FP8 maths with the --fast fp8_matrix_mult option.)

24 GB GDDR6X · 384-bit · 1008 GB/s · Ada Lovelace. Everything that runs on it →

05Questions

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 4090 24 GB?

FP8 (17.3 GB) from Kijai/WanVideo_comfy_fp8_scaled.

FP8 or Q8_0 for Wan 2.2 Animate on the RTX 4090 24 GB?

FP8 (17.3 GB): the RTX 4090 24 GB computes it natively, while Q8_0 (18.7 GB) is unpacked on the fly.

How much do I need to download for Wan 2.2 Animate on the RTX 4090 24 GB?

25.6 GB: Wan2_2-Animate-14B_fp8_scaled_e4m3fn_KJ_v2.safetensors, umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors, clip_vision_h.safetensors.