Can the RTX 5070 Laptop 8 GB run Wan 2.1 VACE 14B?
Not entirely. Even Q4_K_M is 8.4 GB over 8 GB, so ComfyUI keeps part of it in system RAM.
The smallest sensible file, Q4_K_M (11.6 GB), needs about 16.4 GB - 8.4 GB more than RTX 5070 Laptop 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.
01With 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.
02Every Wan VACE 14B file on 8 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 34.7 GB | 39.5 GB | 31.5 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · QuantStack | 18.7 GB | 23.5 GB | 15.5 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · QuantStack | 14.5 GB | 19.3 GB | 11.3 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · QuantStack | 13.0 GB | 17.8 GB | 9.8 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M ← GGUF · QuantStack | 11.6 GB | 16.4 GB | 8.4 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_S GGUF · QuantStack | 7.8 GB | 12.6 GB | 4.6 GB too big | 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.
03What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | Wan2.1_14B_VACE-Q4_K_M.gguf Q4_K_M · QuantStack/Wan2.1_14B_VACE-GGUF | models/unet | 11.6 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 | 18.6 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 VACE 14B on a RTX 5070 Laptop 8 GB, send your time per image and peak VRAM and it will appear here, credited.
05About the RTX 5070 Laptop 8 GB
The RTX 5070 Laptop 8 GB is a Blackwell GPU with FP8 and FP4 hardware: ComfyUI computes Comfy-Org's FP8 files natively here, and NVFP4 files (where a model offers them) are faster still. As a laptop GPU it runs at a lower power limit than desktop cards (50–100 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.
8 GB GDDR7 · 128-bit · 384 GB/s · Blackwell · 50–100 W. Everything that runs on it →
06Questions
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 5070 Laptop 8 GB?
Q4_K_M (11.6 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 5070 Laptop 8 GB?
18.6 GB: Wan2.1_14B_VACE-Q4_K_M.gguf, umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors.