AWQ (Activation-aware Weight Quantization)
Efficient LLM quantization preserving important weight channels.
About
AWQ, Activation-aware Weight Quantization from MIT HAN Lab, compresses large language and multimodal models to 3 or 4-bit weights by protecting the small fraction of salient weight channels identified from activation statistics, preserving more quality than naive quantization at the same bit-width. It pairs with the TinyChat runtime for efficient 4-bit inference, including vision-language models. Released under the MIT license.
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Details
- Category
- Model Training & Fine-Tuning
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Intermediate (3/5)
- License
- MIT
- Minimum VRAM
- 8 GB
- Added
- Apr 3, 2026
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