MiniMaxAI
Text Generation
MiniMax-M3
MiniMax-M3 is MiniMax’s frontier multimodal coding and agentic model, built on the MiniMax Sparse Attention (MSA) architecture. It supports up to a 1M-token context window and accepts image and video inputs. The model is designed for code generation, agentic workflows, tool use, long-context understanding, and multi-step reasoning, showing strong performance on benchmarks such as SWE-Bench Pro, Terminal-Bench 2.1, and MCP Atlas....
總上下文：
1049K
最大輸出：
131K
輸入：
$
0.3
/ M Tokens
輸入：
$
text
/ M Tokens
輸出：
$
1.2
/ M Tokens
MiniMaxAI
Text Generation
MiniMax-M2.5
MiniMax-M2.5 is MiniMax's latest large language model, extensively trained with reinforcement learning across hundreds of thousands of complex real-world environments. Built on a 229B-parameter MoE architecture, it achieves SOTA performance in coding, agentic tool use, search, and office work, scoring 80.2% on SWE-Bench Verified with 37% faster inference than M2.1...
總上下文：
197K
最大輸出：
131K
輸入：
$
0.3
/ M Tokens
輸入：
$
text
/ M Tokens
輸出：
$
1.2
/ M Tokens
