video model · wan · Windows
WA Can I run Wan 2.1 T2V 1.3B on Nvidia GeForce RTX 4060 Ti (16GB)?
Yes. Wan 2.1 T2V 1.3B runs on Nvidia GeForce RTX 4060 Ti (16GB) at Q4 GGUF (~6 GB of ~15 GB usable).
Runs at Q4 GGUF using ~6 GB of ~15 GB usable.
- Peak VRAM
- ~6 GB
- Usable on device
- ~15 GB
- Device memory
- 16 GB
- Quant
- Q4 GGUF
How to run it
Use ComfyUI or Diffusers at Q4 GGUF. The big text encoder is loaded to encode your prompt, then offloaded before generation, which is why peak VRAM stays near the backbone size rather than the sum of every file.
- Type
- video (DIT)
- Parameters
- 1.3B
- Peak VRAM
- ~6 GB at Q4 GGUF
- Resolution
- 832×480 (480p)
- License
- Apache-2.0
- Memory
- 16 GB vram
- Usable for weights
- ~15 GB
- Best runtime
- Ollama (CUDA) / llama.cpp CUDA
You could also run
Run Wan 2.1 T2V 1.3B on other hardware
FAQ
Can Nvidia GeForce RTX 4060 Ti (16GB) run Wan 2.1 T2V 1.3B?
Yes. Wan 2.1 T2V 1.3B runs on Nvidia GeForce RTX 4060 Ti (16GB) at Q4 GGUF (~6 GB of ~15 GB usable).
How much VRAM does Wan 2.1 T2V 1.3B need?
Nvidia GeForce RTX 4060 Ti (16GB) has room to spare. At Q4 GGUF the realistic peak is ~6 GB of VRAM, versus ~20 GB with every component kept resident (no offload). With aggressive CPU offload it drops to ~5 GB, much slower.
What do I use to run Wan 2.1 T2V 1.3B locally?
Wan 2.1 T2V 1.3B runs in ComfyUI or Diffusers. It loads as a video diffusion checkpoint plus its text encoder and VAE, not a single chat command.
Sources
VRAM figures are sourced peak-usage anchors at the noted quant, validated 2026-06-15. See methodology.