video model · wan · Windows
WA Can I run Wan 2.2 TI2V 5B on Nvidia GeForce RTX 4090 (24GB)?
Yes. Wan 2.2 TI2V 5B runs on Nvidia GeForce RTX 4090 (24GB) at Q4 GGUF (~8 GB of ~23 GB usable).
Runs at Q4 GGUF using ~8 GB of ~23 GB usable.
- Peak VRAM
- ~8 GB
- Usable on device
- ~23 GB
- Device memory
- 24 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
- 5B
- Peak VRAM
- ~8 GB at Q4 GGUF
- Resolution
- 1280×704 (720p)
- License
- Apache-2.0
- Memory
- 24 GB vram
- Usable for weights
- ~23 GB
- Best runtime
- vLLM (Linux) / Ollama (CUDA)
You could also run
Run Wan 2.2 TI2V 5B on other hardware
FAQ
Can Nvidia GeForce RTX 4090 (24GB) run Wan 2.2 TI2V 5B?
Yes. Wan 2.2 TI2V 5B runs on Nvidia GeForce RTX 4090 (24GB) at Q4 GGUF (~8 GB of ~23 GB usable).
How much VRAM does Wan 2.2 TI2V 5B need?
Nvidia GeForce RTX 4090 (24GB) has room to spare. At Q4 GGUF the realistic peak is ~8 GB of VRAM, versus ~24 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 2.2 TI2V 5B locally?
Wan 2.2 TI2V 5B 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.