---
id: "minimax/minimax-m2"
also: ["minimax/minimax-m2", "MiniMaxAI/MiniMax-M2", "hf/MiniMaxAI/MiniMax-M2", "requesty/minimax/minimax-m2", "vercel/minimax/minimax-m2"]
card_usd_per_m: "0.255 in, 1.02 out, at minimax/fp8"
cheapest_list_usd_per_m: "0.255 in, 1.02 out, at minimax/fp8 on openrouter"
cheapest_effective_usd_per_m: "0.255 in, 1.0196 out, at minimax/fp8 on openrouter"
context: 204800
max_output: 176947
input: ["text"]
output: ["text"]
released: "2025-10-23"
params: ["frequency_penalty", "include_reasoning", "logprobs", "max_tokens", "presence_penalty", "reasoning", "repetition_penalty", "response_format", "seed", "stop", "structured_outputs", "temperature", "tool_choice", "tools", "top_k", "top_logprobs", "top_p"]
endpoints: 8
gateways: "openrouter (3), hf (2), vercel (2), requesty (1)"
no_training: 4
trains: 0
retains_prompts: 0
intelligence: 18.6000
---
# 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.