MiniMax M2.7
MiniMax M2.7 is a 230B parameter MoE model (10B active) utilizing RoPE and QK RMSNorm. It features recursive self-optimization, updating its own memory to execute highly complex software engineering tasks.
Leaderboards
Average Score combining domain-specific Autobench scores; Higher is better
Performance vs. Industry Average
Intelligence
MiniMax M2.7 is of higher intelligence compared to average (2.9), with an intelligence score of 3.0.
Price
MiniMax M2.7 is cheaper compared to average ($0.75 per 1M Tokens) with a price of $0.10 per 1M Tokens.
Latency
MiniMax M2.7 has a lower average latency compared to average (44.25s), with an average latency of 27.07s.
P99 Latency
MiniMax M2.7 has a lower P99 latency compared to average (126.46s), taking 57.54s to receive the first token at P99 (TTFT).
Context Window
MiniMax M2.7 has a smaller context window than average (406k tokens), with a context window of 205k tokens.