MiniMax M1 Description‍

MiniMax M1 is an open-weight Mixture-of-Experts transformer with 456B total parameters and up to 1 million tokens of context. With 80K output capacity, it is purpose-built for massive input processing, logical analysis, and deep code reasoning. Ideal for RAG pipelines, legal and scientific workflows, and agentic tools.

‍Technical Specification

Technical Specification

• Context Window: 1,000,000 tokens
• Output Capacity: Up to 80,000 tokens
• Architecture: Sparse MoE Transformer with Lightning Attention
• Parameters: 456B (45B active per token)
• API Pricing:
  • Input tokens: $0.5 or $1.4 per million tokens (tiered)
  • Output tokens: $2.3 per million tokens

Performance Metrics

Key Capabilities

• Full-scale document and codebase comprehension across million-token inputs
• Fast inference and optimized MoE routing
• Efficient serving and compatibility
• Supports tool use and planning in agentic workflows

Optimal Use Cases

• Code Engineering: Process and refactor large repositories in a single pass
• Document Analytics: Perform reasoning over legal, technical, or regulatory data
• RAG Systems: Use as a long-context backend for question answering
• Mathematical Reasoning: Step-by-step symbolic and logical analysis

Code Samples

Comparison with Other Models

• Vs. GPT-4o: M1 offers 1M context tokens vs GPT-4o’s 128K; better for large inputs
• Vs. Claude 4 Opus: M1 provides more context (1M vs 128K); both excel in reasoning
• Vs. Gemini 2.5 Pro: M1 leads in token capacity and scale for structured inputs

Limitations

• No vision or multimodal input support
• No fine-tuning API exposed
• Some tools/platforms may require manual integration

API Integration

Accessible via AI/ML API. Documentation: available here.