MinimaxMinimax·text

MiniMax M2.5

CodeReasoningWeb searchFunction calling
Quick reference
MiniMax M2.5 — TLDR
  • 🆕 MiniMax's productivity-focused LLM optimized for coding and agentic workflows.
  • 🧠 Trained via large-scale RL across 200,000+ real-world environments.
  • 📏 Catalog lists a 198K-token context window for long tasks.
  • 🔧 Supports function calling, web search, and multi-step tool use.
  • 🎯 Vendor-reported 80.2% on SWE-Bench Verified, 51.3% Multi-SWE-Bench.
  • ⚡ Completes SWE-Bench Verified roughly 37% faster than M2.1.
  • 📚 "Spec-writing" behavior: plans architecture before writing code.
  • 💬 Strong on office workflows like Word, PowerPoint, Excel modeling.
💰 Best price on AntSeed
FREE / FREE
per 1M · cheapest in / out
📏 Context
198K tokens
🐜 Sellers
21
advertising on AntSeed
Provider

MiniMax is an AI company building generative models across multiple modalities, with a focus that spans both language understanding and audio creation. Their rapid release cadence in early 2026—delivering several new models within just a few months—reflects an ambitious and…

Explore 3 more models by Minimax
About this model

MiniMax M2.5, released in February 2026, is a text model from MiniMax built for coding, agentic tool use, and office productivity. According to MiniMax, it was extensively trained with reinforcement learning across more than 200,000 complex real-world environments using the company's Forge agent-native RL framework and CISPO algorithm, with a process-reward mechanism for monitoring generation quality in long-context agent rollouts. The catalog lists a 198K-token context window plus reasoning, code-optimization, function-calling, and web-search capabilities.

Against its same-family predecessor M2.1, MiniMax reports concrete gains. On the provider's reported SWE-Bench Verified, M2.5 scores 80.2% while completing the evaluation about 37% faster than M2.1—end-to-end runtime dropping from 31.3 to 22.8 minutes and tokens per task falling from 3.72M to 3.52M. MiniMax also reports 51.3% on Multi-SWE-Bench and 76.3% on BrowseComp with context management. A notable behavioral change is M2.5's tendency to decompose and plan features, structure, and UI like a software architect before coding.

MiniMax positions M2.5 for the full development lifecycle across Web, Android, iOS, Windows, and Mac, and for workspace tasks such as financial modeling and report generation. A higher-throughput M2.5-highspeed variant is also offered.

M2.5 was later succeeded within the family by [[sibling:minimax-m27|MiniMax M2.7]], [[sibling:minimax-m3|MiniMax M3]], and [[sibling:minimax-m3-preview|MiniMax M3 Preview]], all sharing the same coding-and-agentic focus. For deployment, MiniMax recommends vLLM or SGLang.

Sources
minimax.ioMiniMax M2.5: Built for Real-World Productivity. - MiniMax News | MiniMax· minimax.iohuggingface.coMiniMaxAI/MiniMax-M2.5 · Hugging Face· huggingface.co

This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.

Sellers serving MiniMax M2.5 (21)
SellerReputationInput $/MCached $/MOutput $/MCategoriesAPI

"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens, not settled amounts). Reputation = on-chain trust (0-100). Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase.