Inferact is an API launch partner for MiniMax M3.1 Flash! 🎉 We're working with @MiniMax_AI on production inference for its latest model, built for multi-step automation, real-codebase engineering and visual reasoning. M3.1 Flash scored 29.6 on Agents’ Last Exam (ALE), alongside 72.5% on AutomationBench-AA and 73.67% on DeepSWE—capabilities that matter when agents need to plan work, use tools and carry tasks through. Our contribution is the serving stack: bringing our vLLM engineering and the Inferact Platform to the collaboration. Thanks to the MiniMax team for the partnership. Explore the model and API integration: platform.minimax.io/docs/gui…

Today we launch SGLang-TorchTPU, built with @Google TPU team and Meta @PyTorch team. We’re excited to see it powering production inference at Meta! SGLang-TorchTPU is a TPU plugin for SGLang that brings: - Top open models on TPU: Muse Spark Open, GLM-5.3 Flash, Kimi K3, Ling 3.1 Flash, MiniMax H3 - SGLang’s production features for large agentic workloads - Custom MegaKernel: Muse Spark Open hits 770 tok/s decode at bs=1 on InferenceX 8K/1K SGLang-TorchTPU is available now: github.com/sgl-project/sglan…

We just tried @MiniMax_AI's M3.1 Flash in our SGLang Omni cascaded voice interaction system, and the experience was genuinely impressive! 🐰🚀 Our original pipeline was Qwen3-ASR → Qwen3 LLM → Qwen3-TTS. We replaced the locally hosted LLM with the MiniMax M3.1 Flash API while keeping the rest of the pipeline unchanged, and recorded a demo to see how it performs in real conversations. The results were excellent. M3.1 Flash responded incredibly fast, understood our questions well, and consistently delivered sharp, concise, and direct answers. The conversation felt remarkably smooth and natural. One thing I increasingly appreciate about voice agents is that intelligence alone isn't enough. Unlike text, users can't easily skim an audio response. A model that understands what you need and gets straight to the point can make a huge difference to the overall interaction experience. This is also what makes the modular architecture of SGLang Omni so exciting to me. We can swap individual components, connect local speech models with frontier LLM APIs, and immediately explore how different models change the end-to-end interaction experience. Huge congrats to the MiniMax team! Really impressive work, and we're excited to explore more together. 🔥

MiniMax M3.1 Flash from @MiniMax_AI is now on Runware 🧠 - Text, image & video input - 1M context, up to 524K output tokens - Adjustable reasoning depth - 42 on the Artificial Analysis Intelligence Index - 72.5% AutomationBench-AA, 73.7% DeepSWE - Cheaper per token than MiniMax M3

MiniMax M3.1 Flash is now #1 on our search capabilities leaderboard for efficiency. It delivers web research performance with Parallel Search similar to DeepSeek V4.1 Flash (1017) at ~3x lower cost.

MiniMax M3.1 Flash vs Claude Opus 5.5 in cinematic absurdity. Two takes on the impossible, made with Higgsfield.

MiniMax M3.1 Flash (aka Space Bunny) is now live and FREE in Command Code for limited time! · 1M token context window · Frontier level coding performance · Available all plans, all subscribers

MiniMax M3.1 Flash, aka Space Bunny, is now available on GMI Built for coding, agentic workflows, and computer use 70% lower agentic task costs, 73.7% on DeepSWE v1.1, 82% on CyberGym Run it now 👇

MiniMax M3.1 Flash goes toe-to-toe with Opus and GPT on coding at ~25x lower cost. This was the model behind Space Bunny, the stealth model that’s been topping usage leaderboards recently. Free in Cline now!

Stealth model reveal 🐰 Space Bunny was OpenRouter’s #1 model for 10 straight days, processing 56.7T tokens! The most of any stealth model we’ve run. Space Bunny hopped off OpenRouter on Oct 5. It's back today as @MiniMax_AI's M3.1 Flash, and it's free for the next 72 hours.

Space Bunny was MiniMax M3.1 Flash #1 on OpenCode for 12 consecutive days, 106T tokens served Now available on OpenCode, free for the next 3 days