Product Launchmoeagentscode generationtool calling
MiniMax-M2 Delivers Efficient Agentic Coding Model
8.0
MiniMaxAI's MiniMax-M2 is a 230B-parameter Mixture of Experts model that activates only 10B parameters per token, offering agentic and coding capabilities with reduced inference cost. The model reports competitive benchmarks (BrowseComp 44.0; Terminal-Bench 46.3; SWE-bench Verified 69.4) and supports tool-calling, interleaved-thinking tags, and vllm-based deployment for cost-sensitive developer workflows.
Key Points
- 1Implements 230B-parameter Mixture-of-Experts model activating only 10B parameters per token during inference.
- 2Delivers competitive agentic and coding benchmarks: BrowseComp 44.0, Terminal-Bench 46.3, SWE-bench Verified 69.4.
- 3Enables practitioners to deploy cost-efficient agents with tool-calling, vllm serving, and interleaved-thinking support.
Scoring Rationale
Strong practical deployment details and competitive agent benchmarks, but limited radical novelty over existing MoE agent models.
Sources
Public references used for this report.
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