video model · wan · Windows
Can I run Wan 2.2 T2V A14B on Nvidia GeForce RTX 4060 Ti (16GB)?
Needs ~16 GB at Q4 GGUF, but only ~15 GB is usable on Nvidia GeForce RTX 4060 Ti (16GB). With aggressive CPU offload it can run on as little as ~8 GB, much slower.
Needs ~16 GB at Q4 GGUF, but only ~15 GB is usable on Nvidia GeForce RTX 4060 Ti (16GB). With aggressive CPU offload it can run on as little as ~8 GB, much slower.
The gap is about 1 GB: Wan 2.2 T2V A14B needs roughly 16 GB and Nvidia GeForce RTX 4060 Ti (16GB) leaves only about 15 GB usable for a model. The lightest tracked hardware that runs Wan 2.2 T2V A14B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Wan 2.2 T2V A14B on Nvidia GeForce RTX 4090 (24GB).
- Peak VRAM
- ~16 GB
- Usable on device
- ~15 GB
- Device memory
- 16 GB
- Quant
- Q4 GGUF
- Type
- video (DIT)
- Parameters
- 27B (MoE, 14B active)
- Peak VRAM
- ~16 GB at Q4 GGUF
- Resolution
- 1280×720 (720p)
- License
- Apache-2.0
- Memory
- 16 GB vram
- Usable for weights
- ~15 GB
- Power draw
- ~165 W
- Best runtime
- Ollama (CUDA) / llama.cpp CUDA
What you can run instead
Run Wan 2.2 T2V A14B on other hardware
FAQ
Can Nvidia GeForce RTX 4060 Ti (16GB) run Wan 2.2 T2V A14B?
Needs ~16 GB at Q4 GGUF, but only ~15 GB is usable on Nvidia GeForce RTX 4060 Ti (16GB). With aggressive CPU offload it can run on as little as ~8 GB, much slower.
How much VRAM does Wan 2.2 T2V A14B need?
Nvidia GeForce RTX 4060 Ti (16GB) does not have enough memory. At Q4 GGUF the realistic peak is ~16 GB of VRAM, versus ~80 GB with every component kept resident (no offload). With aggressive CPU offload it drops to ~8 GB, much slower.
What do I use to run Wan 2.2 T2V A14B locally?
Wan 2.2 T2V A14B 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 2026-08-03. See methodology.