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MiniCPM5-2B is a family of compact language models developed for local, on-device, and resource-constrained AI workloads. The current MiniCPM5 series includes dense 1B and 2B models designed to deliver strong capability with a small deployment footprint. MiniCPM5-2B provides a 131K-token context window and targets assistants, coding agents, reasoning, tool use, and other agentic tasks. The repository includes base, supervised fine-tuned, and deployment-ready model variants. Quantized releases are available in formats such as GGUF, MLX, GPTQ, and DSpark. It also provides fine-tuning, quantization, deployment, and agent-skill resources for adapting models to different environments. Earlier MiniCPM releases explore sparse attention, mixture-of-experts designs, long-context modeling, and efficient edge inference.
Features
- Compact 1B and 2B on-device language models
- 131K-token native context support in MiniCPM5-2B
- Coding, mathematics, reasoning, and tool-use capabilities
- Base, SFT, mid-training, and deployment variants
- GGUF, MLX, GPTQ, and other quantized formats
- Fine-tuning, quantization, deployment, and agent-skill resources
Project Samples
