DFloat11 / OmniGen2-transformer-DF11

DFloat11 Compressed Model: OmniGen2/OmniGen2 Transformer

This is a DFloat11 losslessly compressed version of the original OmniGen2/OmniGen2 model. It reduces model size by 32% compared to the original BFloat16 model, while maintaining bit-identical outputs and supporting efficient GPU inference .

📊 Performance Comparison

🔧 How to Use

A complete usage guide is available in our GitHub repository (forked from the official OmniGen2 repository).

👉 https://github.com/LeanModels/OmniGen2-DFloat11 👈

🔍 How It Works

We apply Huffman coding to losslessly compress the exponent bits of BFloat16 model weights, which are highly compressible (their 8 bits carry only ~2.6 bits of actual information). To enable fast inference, we implement a highly efficient CUDA kernel that performs on-the-fly weight decompression directly on the GPU.

The result is a model that is ~32% smaller , delivers bit-identical outputs , and achieves performance comparable to the original BFloat16 model.

Learn more in our research paper .

📄 Learn More

• Paper : 70% Size, 100% Accuracy: Lossless LLM Compression for Efficient GPU Inference via Dynamic-Length Float
• GitHub : https://github.com/LeanModels/DFloat11
• HuggingFace : https://huggingface.co/DFloat11