About
MiniMind is an ultra-lightweight open-source project designed to democratize LLM training by enabling users to build models as small as 64M from scratch. Developed natively in PyTorch, it aligns with the Qwen3 architecture and supports the full training pipeline, including Pretraining, SFT, LoRA, RLHF, and Agentic RL (GRPO/CISPO). It provides a 'white-box' learning experience, allowing reproduction on consumer GPUs at minimal cost. The ecosystem includes multimodal variants and reasoning capabilities, making it ideal for edge deployment and educational research.
Features
- Full-lifecycle reproduction
- Ultra-lightweight (Dense & MoE support)
- Cross-platform compatibility
- Native Tool-Use & Reasoning
- Low hardware requirements
Supported Platforms
Links
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