Wan2.2-I2V-A14B-Diffusers
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
Copy-paste - running in under a minute
vllm serve Wan-AI/Wan2.2-I2V-A14B-DiffusersNew to this? Start with Ollama · serve to many users with vLLM.
Deep dive
Notes, sources, and the full write-up
Wan2.2-I2V-A14B-Diffusers is an open-weight video generation model from Wan-AI, published on Hugging Face in July 2025. It has 14.3B parameters and is released under the apache-2.0 license.
HardwareLink to this section
At full FP16 precision the weights need about 29 GB of memory; 8-bit quantization brings that to roughly 15 GB. Check the VRAM tiers above to see which GPUs fit it.
PopularityLink to this section
Wan2.2-I2V-A14B-Diffusers had 182,173 downloads on Hugging Face in the last month and has 324 likes.
Run it locallyLink to this section
The weights are on Hugging Face and load with Hugging Face Diffusers (or ComfyUI). Follow the model card for the exact setup and license terms.
Frequently asked
Quick answers to common questions
How much VRAM does Wan2.2-I2V-A14B-Diffusers need?
Wan2.2-I2V-A14B-Diffusers with 14.3B parameters needs approximately 8 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Wan2.2-I2V-A14B-Diffusers better than other Wan-AI models?
Wan2.2-I2V-A14B-Diffusers has 14.3B parameters with 8,192 context - a strong choice for video-generation, image-to-video.
What license is Wan2.2-I2V-A14B-Diffusers under?
Wan2.2-I2V-A14B-Diffusers is released under the apache-2.0 license, making it suitable for most commercial and personal projects.
What hardware runs Wan2.2-I2V-A14B-Diffusers well?
With 14.3B parameters, Wan2.2-I2V-A14B-Diffusers requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Wan2.2-I2V-A14B-Diffusers?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~10 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
What models compete with Wan2.2-I2V-A14B-Diffusers?
Wan2.2-I2V-A14B-Diffusers competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec