

MiniMax (official)
1.2K posts

@MiniMax_AI
Agent: @MiniMaxAgent Token Plan: https://t.co/BDCycxepZw API: https://t.co/fHRdSV7BwZ Discord: https://t.co/uYnFNkYh7y




If you're in SF for GTC, this weekend matters. We're bringing together a curated group of AI founders & builders for an afternoon of high-signal conversations, including: - a keynote from MiniMax cofounder (yes, Yeyi is in town 🙌) - a first look at our latest model (a LOT of people have been asking) - and a room full of builders actually shipping If you're building, you won't want to miss this one. RSVP 👇 luma.com/aic-sf-3-21


MiniMax M2.7 is real deal man I have made a complete website with proper fan physics and fibre physics this looks so good @MiniMax_AI i am waiting for the next update man , i want a big model next cook it for us Prompt is in comment for normal paper receipt physics sim



Introducing MiniMax-M2.7, our first model which deeply participated in its own evolution, with an 88% win-rate vs M2.5 - Production-Ready SWE: With SOTA performance in SWE-Pro (56.22%) and Terminal Bench 2 (57.0%), M2.7 reduced intervention-to-recovery time for online incidents to 3-min on certain occasions. - Advanced Agentic Abilities: Trained for Agent Teams and tool search tool, with 97% skill adherence across 40+ complex skills. M2.7 is on par with Sonnet 4.6 in OpenClaw. - Professional Workspace: SOTA in professional knowledge, supports multi-turn, high-fidelity Office file editing. MiniMax Agent: agent.minimax.io API: platform.minimax.io Token Plan: platform.minimax.io/subscribe/toke…

So I got early access to Minimax-M2.7 and it is insane this model is a builder's dream I made a space invader game on a raspberry pi here you go a look into it.

MiniMax M2.7 is live on Runware on Day0! 🚀 - full end-to-end project delivery - self-evolving architecture: 30% performance gains across 100+ iterations - 97% skill adherence rate across 40+ complex tasks - 56.22% on SWE-Pro, 55.6% on VIBE-Pro, 57.0% on Terminal Bench 2

MiniMax M2.7 is now in AdaL. What stood out to us was Agent Teams. Agents can take different roles, search tools, challenge each other’s reasoning, and work through complex coding tasks together. ~2.5% of Sonnet pricing. ~5% of Opus pricing

My first test of MiniMax M2.7 this made 3d fibre physics with all the specs of m2.7 is written

MiniMax-M2.7 just landed in MiniMax Agent. The model helped build itself. Now it's here to build for you. ↓ Try Now: agent.minimax.io

My first test of MiniMax M2.7 this made 3d fibre physics with all the specs of m2.7 is written

Early testers are saying that M2.7 has big improvements in emotional intelligence and character consistency 👀



If you're in SF for GTC, this weekend matters. We're bringing together a curated group of AI founders & builders for an afternoon of high-signal conversations, including: - a keynote from MiniMax cofounder (yes, Yeyi is in town 🙌) - a first look at our latest model (a LOT of people have been asking) - and a room full of builders actually shipping If you're building, you won't want to miss this one. RSVP 👇 luma.com/aic-sf-3-21



Introducing MiniMax-M2.7, our first model which deeply participated in its own evolution, with an 88% win-rate vs M2.5 - Production-Ready SWE: With SOTA performance in SWE-Pro (56.22%) and Terminal Bench 2 (57.0%), M2.7 reduced intervention-to-recovery time for online incidents to 3-min on certain occasions. - Advanced Agentic Abilities: Trained for Agent Teams and tool search tool, with 97% skill adherence across 40+ complex skills. M2.7 is on par with Sonnet 4.6 in OpenClaw. - Professional Workspace: SOTA in professional knowledge, supports multi-turn, high-fidelity Office file editing. MiniMax Agent: agent.minimax.io API: platform.minimax.io Token Plan: platform.minimax.io/subscribe/toke…

Open source continues to catch up with closed source MiniMax 2.7 just dropped and will likely become the most used LLM on Claw in days 🚀

MiniMax M2.7 is ranked #8 in Code Arena. It’s also the most cost-efficient of the top 10 at $0.30 / $1.20 per MToken. Congrats to the team at @MiniMax_AI 👏