Fastwan AI FAQ: Common Questions and Troubleshooting Guide
Find answers to the most common questions about Fastwan AI video generation, from hardware requirements to model optimization and troubleshooting.
What is Fastwan AI and how does it work?
Fastwan AI is a breakthrough video generation technology that uses sparse distillation to create 5-second videos in just 5 seconds. It combines video sparse attention (VSA) with distribution matching distillation (DMD) to reduce traditional 50-step generation to just 3 steps while maintaining quality.
What hardware do I need to run Fastwan AI?
Fastwan AI supports various hardware configurations: NVIDIA H200 for optimal performance (5-16 seconds), RTX 4090 for consumer use (21-45 seconds), and Apple Silicon through the FastVideo framework. Minimum requirements include 8GB VRAM for smaller models.
How does Fastwan AI compare to traditional video generation?
Fastwan AI is up to 50x faster than traditional methods. Where conventional models need 50 denoising steps taking minutes, Fastwan AI achieves similar quality in 3 steps taking seconds, thanks to sparse distillation technology.
What video resolutions and formats are supported?
FastWan2.1-1.3B generates 480P videos, while FastWan2.2-5B creates 720P videos. All models produce 5-second clips at 24fps. Output formats include standard video files compatible with most video editing software.
Is Fastwan AI free to use?
Yes, Fastwan AI is released under the Apache-2.0 license, making it completely free for commercial and research use. All model weights, training recipes, and datasets are openly available.
Can I fine-tune Fastwan AI models?
Absolutely. The complete training recipes and code are available, allowing you to fine-tune models on your own datasets. Training FastWan2.1-1.3B costs approximately $2,603 using cloud H200 instances.
What types of prompts work best?
Effective prompts combine clear scene descriptions with motion directions. Examples: 'A golden retriever running through a sunny meadow' works better than just 'dog'. Include camera movement, lighting, and specific actions for best results.
How do I optimize generation speed?
Use torch.float16 precision, keep models in GPU memory, enable torch.compile, and use appropriate batch sizes. Ensure CUDA is properly installed and consider using the sparse attention optimizations.
Still Have Questions?
If you need additional help or have specific technical questions, the Fastwan AI community is here to support you.
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