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OpenBMBFebruary 11, 2026

MiniCPM-SALA

Open Source
LLMs
ML

Explore MiniCPM-SALA

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### 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

Pricing
Open-source and freely available
Cost structure
Version
1.0
Current release version
Hardware
NVIDIA RTX 5090 GPU or higher
Compute requirements
Category
Open Source
Licensing model
Region
China
Primary region

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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