MiniMax: MiniMax M2Active

minimax/minimax-m2

MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning, tool use, and multi-step task execution while maintaining low latency and deployment efficiency. The model excels in code generation, multi-file editing, compile-run-fix loops, and test-validated repair, showing strong results on SWE-Bench Verified, Multi-SWE-Bench, and Terminal-Bench. It also performs competitively in agentic evaluations such as BrowseComp and GAIA, effectively handling long-horizon planning, retrieval, and recovery from execution errors. Benchmarked by Artificial Analysis, MiniMax-M2 ranks among the top open-source models for composite intelligence, spanning mathematics, science, and instruction-following. Its small activation footprint enables fast inference, high concurrency, and improved unit economics, making it well-suited for large-scale agents, developer assistants, and reasoning-driven applications that require responsiveness and cost efficiency.

By:MiniMaxInput Type:Output Type:Publish time:2025-10-27

Providers

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ProviderCache Hit RateContext

MiniMax

minimax

17.6%$0.3/ M tokens$1.2/ M tokensRead:0.03/ M tokensWrite:0.375/ M tokens204.8K--

Uptime

24hours

Direct request success rate on AI Gateway and per-provider.

Throughput

24hours

P50 throughput on live AI Gateway traffic, in tokens per second (TPS).

Latency

24hours

P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds.

Activity

Token volume and request traffic to this model over time.

Token Consumption

Benchmarks

Scores on standardized evaluations. Higher percentages are better — and rank percentile shows

Metrics sourced fromArtificial Analysis

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for. View All

Token Ranking

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