minimax-m2

MiniMax-M2 is a high-efficiency MoE (Mixture-of-Experts) model designed specifically for developers building autonomous agents and complex coding pipelines. While it boasts a massive 230B total parameter architecture, it only activates 10B parameters per token, striking a strategic balance between frontier-level reasoning and low-latency execution. For engineers, this means you get the cognitive depth required for multi-step logic and code generation without the prohibitive inference costs typically associated with massive dense models. Its 204k context window makes it a viable candidate for RAG-heavy applications and analyzing entire codebases. Unlike general-purpose chat models that prioritize conversational fluff, M2 is tuned for the structured, iterative reasoning required in agentic workflows, making it a strong competitor for developers looking to deploy reliable, task-oriented AI agents via API.