AI Video Generation Hardware Requirements: CogVideoX, Mochi & Wan Compared
Video generation is the most VRAM-demanding category of AI models. Even "small" video models need more memory than most large language models. Here's what you actually need.
Hardware Requirements
| Model | Parameters | Min VRAM | Recommended | Output |
|---|---|---|---|---|
| AnimateDiff | 0.4B | 8GB | 12GB | 16-frame animation |
| Wan 2.1 1.3B | 1.3B | 8GB | 12GB | Short clips, 480p |
| CogVideoX 2B | 2B | 6GB (INT8) | 16GB | Short clips |
| CogVideoX 5B | 5B | 12GB (INT8) | 24GB | Better quality |
| Mochi 1 | 10B | 24GB | 48GB+ | High quality, realistic |
The Entry Point: CogVideoX 2B
CogVideoX 2B with INT8 quantization is the most accessible option, fitting in just 6GB VRAM. Quality is limited but it demonstrates the technology. With 16GB VRAM, you get a significantly better experience.
The Quality Tier: 24GB VRAM
At 24GB (RTX 4090), you can run CogVideoX 5B and Mochi 1 with optimizations. This is where video generation starts to look genuinely impressive.
When Cloud Makes Sense
Video generation is perhaps the strongest use case for cloud GPUs. A single RTX 4090 on RunPod costs $0.44/hour — generate a few videos and shut it down. Much more economical than buying a $1600 GPU for occasional use.
Browse all video generation models and check your hardware compatibility on our model browser.