Can the RTX 5060 Ti 16 GB run Wan 2.1 VACE 14B?
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 Q3_K_S (7.8 GB).
Take Q3_K_S (7.8 GB). In use it comes to about 12.6 GB, with 3.4 GB left over on 16 GB. Quality: noticeable loss of detail. For better quality, Q4_K_M (11.6 GB) also runs, with about 0.4 GB spilling into system RAM - a little slower, still practical.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | Wan2.1_14B_VACE-Q3_K_S.gguf Q3_K_S · QuantStack/Wan2.1_14B_VACE-GGUF | models/unet | 7.8 GB | Download → |
| Text encoder | umt5_xxl_fp8_e4m3fn_scaled.safetensors UMT5-XXL FP8 (scaled) · Comfy-Org/Wan_2.1_ComfyUI_repackaged | models/text_encoders | 6.7 GB | Download → |
| VAE | wan_2.1_vae.safetensors Wan 2.1 VAE · Comfy-Org/Wan_2.1_ComfyUI_repackaged | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 14.8 GB | |||
Alternatives: UMT5-XXL FP16 (11.4 GB). Sizes from Hugging Face, 2026-10-01.
02Every Wan VACE 14B file on 16 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 34.7 GB | 39.5 GB | 23.5 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · QuantStack | 18.7 GB | 23.5 GB | 7.5 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · QuantStack | 14.5 GB | 19.3 GB | 3.3 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · QuantStack | 13.0 GB | 17.8 GB | spills 1.8 GB | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · QuantStack | 11.6 GB | 16.4 GB | spills 0.4 GB | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_S ← GGUF · QuantStack | 7.8 GB | 12.6 GB | fits · 3.4 GB spare | noticeable loss of detail | Hugging Face → |
“Needed” adds 4 GB of working memory for Wan VACE 14B 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 VACE 14B on a RTX 5060 Ti 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 VACE 14B at 8-bit or better (Q8_0, 18.7 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 5060 Ti 16 GB to the RTX 3090 24 GB → · What changes from the RTX 5060 Ti 16 GB to the RTX 5070 Ti 16 GB → · What changes from the RTX 5060 Ti 16 GB to the RTX 4090 24 GB → · What changes from the RTX 5060 Ti 16 GB to the RTX 5090 32 GB →
05Questions
How much VRAM does Wan VACE 14B need?
Around 12.6 GB with the smallest file (Q3_K_S) and 23.5 GB with an 8-bit file (Q8_0). The full 16-bit file needs about 39.5 GB.
Which Wan VACE 14B file should I download for the RTX 5060 Ti 16 GB?
Q3_K_S (7.8 GB) from QuantStack/Wan2.1_14B_VACE-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
How much do I need to download for Wan VACE 14B on the RTX 5060 Ti 16 GB?
14.8 GB: Wan2.1_14B_VACE-Q3_K_S.gguf, umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors.