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Can the RTX 4090 Laptop 16 GB run Wan Animate 2 (14B)?

Not at full quality. The 16-bit and 8-bit files are too big for the RTX 4090 Laptop 16 GB; the largest that fits is Q3_K_M (8.6 GB).

Video model · 14B16 GB GDDR6 · 256-bit · Ada Lovelace · 80–150 WData 2026-10-01
Tight
Only just.

Take Q3_K_M (8.6 GB). In use it comes to about 13.9 GB, with 2.1 GB left over on 16 GB. Quality: noticeable loss of detail. For better quality, Q4_K_M (11.3 GB) also runs, with about 0.6 GB spilling into system RAM - a little slower, still practical.

Best fileQ3_K_M
File size8.6 GB
VRAM needed~13.9 GB
System RAM32 GB+
Memory map · RTX 4090 Laptop 16 GB13.9 GB / 16 GB
08 GB16 GB
Weights Q3_K_M · 8.6 GBWorking memory · 4.5 GBReserve · 0.8 GBFree · 2.1 GB

Also try the INT8 file (16.7 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 →

01What to download

PartFileFolderSize
ModelWan-Animate-2-14B-TURBO-Q3_K_M.gguf
Q3_K_M · realrebelai/Wan-Animate-2_GGUFs
models/unet8.6 GBDownload →
Text encoderumt5_xxl_fp8_e4m3fn_scaled.safetensors
UMT5-XXL FP8 (scaled) · Comfy-Org/Wan-Animate-2
models/text_encoders6.7 GBDownload →
VAEWan2_1_VAE_bf16.safetensors
Wan 2.1 VAE BF16 (Kijai) · Comfy-Org/Wan-Animate-2
models/vae0.3 GBDownload →
Also neededclip_vision_h.safetensors
CLIP Vision H · Comfy-Org/Wan-Animate-2
models/clip_vision1.3 GBDownload →
Total download · keep about the same free on disk16.8 GB

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

02Every Wan Animate 2 file on 16 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
32.8 GB38.1 GB22.1 GB too bigthe original weightsHugging Face →
INT8
SAFETENSORS · Comfy-Org
16.7 GB22.0 GB6.0 GB too bigpractically identical to the originalHugging Face →
Q8_0
GGUF · realrebelai
18.1 GB23.4 GB7.4 GB too bigpractically identical to the originalHugging Face →
Q6_K
GGUF · realrebelai
14.2 GB19.5 GB3.5 GB too bigvery close to the originalHugging Face →
Q5_K_M
GGUF · realrebelai
12.7 GB18.0 GB2.0 GB too bigclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · realrebelai
11.3 GB16.6 GBspills 0.6 GBgood; some loss in fine detail and textHugging Face →
Q3_K_M ←
GGUF · realrebelai
8.6 GB13.9 GBfits · 2.1 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · realrebelai
6.5 GB11.8 GBfits · 4.2 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 4.5 GB of working memory for Wan Animate 2 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 Animate 2 on a RTX 4090 Laptop 16 GB, send your time per image and peak VRAM and it will appear here, credited.

04With more VRAM

With 24 GB you could run Wan Animate 2 at 8-bit or better (INT8, 16.7 GB) with no offloading: for example on the RTX 4090 24 GB, RTX 3090 24 GB, RX 7900 XTX 24 GB.

05About the RTX 4090 Laptop 16 GB

The RTX 4090 Laptop 16 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.) As a laptop GPU it runs at a lower power limit than desktop cards (80–150 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.

16 GB GDDR6 · 256-bit · Ada Lovelace · 80–150 W. Everything that runs on it →

06Questions

How much VRAM does Wan Animate 2 need?

Around 11.8 GB with the smallest file (Q2_K) and 22.0 GB with an 8-bit file (INT8). The full 16-bit file needs about 38.1 GB.

Which Wan Animate 2 file should I download for the RTX 4090 Laptop 16 GB?

Q3_K_M (8.6 GB) from realrebelai/Wan-Animate-2_GGUFs. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

How much do I need to download for Wan Animate 2 on the RTX 4090 Laptop 16 GB?

16.8 GB: Wan-Animate-2-14B-TURBO-Q3_K_M.gguf, umt5_xxl_fp8_e4m3fn_scaled.safetensors, Wan2_1_VAE_bf16.safetensors, clip_vision_h.safetensors.