MiniCPM-SALA
### TL;DR
MiniCPM-SALA is a large-scale hybrid language model developed by OpenBMB, integrating sparse and linear attention mechanisms to efficiently handle long-context modeling. Released on February 11, 2026, it is the first model to effectively combine sparse and linear attention for million-token context modeling. ([huggingface.co](https://huggingface.co/openbmb/MiniCPM-SALA?utm_source=openai))
Key Insights & Metrics
Key Features
- Hybrid architecture combining 25% sparse attention and 75% linear attention
- Achieves 3.5× inference speedup over dense baselines
- Supports context lengths up to 1 million tokens
- Utilizes Hybrid Positional Encoding (HyPE) for improved performance
- HALO adaptation for efficient transfer of dense attention capabilities
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