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MiniMax-M2.5 API Benchmarks: Latency, Throughput & Cost

Blog post from Deepinfra

Post Details
Company
Date Published
Author
Deep
Word Count
1,853
Company Posts That Month
34
Language
English
Hacker News Points
-
Post removed?
No
Summary

MiniMax-M2.5 is a cutting-edge large language model released in February 2026, featuring a 230B-parameter Mixture of Experts (MoE) architecture with innovative Lightning Attention, supporting a context window of up to 205,000 tokens. Trained with reinforcement learning across over 200,000 real-world environments, it excels in programming tasks, handling more than 10 coding languages, and is particularly adept at decomposing and planning software architecture. The model achieves top industry benchmark scores, showing a 37% faster performance than its predecessor, M2.1. MiniMax-M2.5 is available through several API providers, with DeepInfra being the standout choice due to its balanced approach of low latency, competitive pricing, and comprehensive feature support. DeepInfra offers a token pricing of $0.44 per million, a latency of 0.56s, and excels in applications requiring rapid response times, such as RAG applications and agentic workflows. Other providers like SambaNova, Together.ai, SiliconFlow, and Fireworks cater to specific needs, such as maximum throughput, lowest latency, cost efficiency, and high speed, respectively, each with unique trade-offs in performance metrics.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
RAG 5 941 216 85 -48%
Real-time 3 6,296 1,346 246 -2%
LLM 2 5,932 1,046 223 -2%
AI Agents 1 4,430 1,100 236 -3%
Reinforcement learning 1 104 49 23 -14%
Vector Search 1 1,739 413 146 -27%
Voice AI 1 2,379 221 38 -3%
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