DFloat11 Compressed Model: Wan-AI/Wan2.1-T2V-14B-Diffusers
This model uses DFloat11 lossless compression. It's 30% smaller than the original BFloat16 model, yet produces bit-identical outputs and runs efficiently on GPUs.
📊 Performance Comparison
| Metric | Wan2.1-T2V-14B (BFloat16) | Wan2.1-T2V-14B (DFloat11) |
|---|---|---|
| Model Size | 28.64 GB | 19.39 GB |
| Peak GPU Memory (2s 480p Video) |
30.79 GB | 22.22 GB |
| Generation Time (an A100 GPU) |
339 seconds | 348 seconds |
🔍 How It Works
We apply Huffman coding to the exponent bits of BFloat16 model weights, which are highly compressible. We leverage hardware-aware algorithmic designs to enable highly efficient, on-the-fly weight decompression directly on the GPU. Find out more in our research paper.
🔧 How to Use
A complete usage guide is available in our GitHub repository: https://github.com/LeanModels/DFloat11/tree/master/examples/wan2.1.
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