@MiniMax_AI

Code: @MiniMaxAgent MiniMax Design: @Hailuo_AI API: https://xitter.cf/t.co/fHRdSV73Hr M Plan: https://xitter.cf/t.co/XfJWSyauda

 San Francisco
minimax.io/
Joined January 2025
  • Tweets2K
  • Following1K
  • Followers128K
271Media
MiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: platform.minimax.io M Plan: minimax.io/m-plan MiniMax Code for desktop: agent.minimax.io/download
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MiniMax (official) retweeted
Minds by Animoca Brands
@hellominds_Oct 20
Congratulations to @MiniMax_AI on launching M3.1 Flash! 🎉 We're proud to be a launch partner from day one. Faster, lighter, and built for volume. Whether you’re building, learning something new or just getting through the day, your Mind is a digital companion that grows with you and helps you unlock what you never thought was possible. Try it out at hellominds.ai.

Minds by Animoca Brands | Personal AI Agents

Put a personal AI agent to work through email and the messaging channels you already use. Minds handles bookings, research and everyday tasks. No coding required.

hellominds.ai
MiniMax (official)
@MiniMax_AIOct 19
MiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: platform.minimax.io M Plan: minimax.io/m-plan MiniMax Code for desktop: agent.minimax.io/download
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Great to have Inferact as an API launch partner for M3.1 Flash! Thanks for bringing your vLLM expertise to the collaboration. Excited to keep building the serving infrastructure for complex agent workloads together.
Inferact
@inferactOct 19
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…

Model Invocation - MiniMax API Docs

MiniMax LLMs, supporting multilingual programming, Agent workflows and complex task scenarios.

platform.minimax.io
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Thank you for bringing H3 to TPUs! Excited to see more open-source work on efficient video inference and what it could enable: faster creative iteration, new interactive experiences, and more ways for developers to build with H3.
SGLang
@sgl_project21h
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…
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Tutorial + code for you to cook with. ⬇️ sglang.io/blog/omni-interact… sglang.io/blog/omni-interact…

Unified Runtime for Full-Duplex Interactive Intelligence with SGLang Omni | SGLang Blog

Graphs, persistent sessions, and model execution unify native full-duplex, turn-based, and cascaded interactive systems in SGLang-Omni.

sglang.io
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MiniMax M3.1 Flash + SGLang Omni: building toward a more interactive generation of voice agents. The shift ahead is from “ask, wait, listen” to conversations people can interrupt, correct, and redirect as a task unfolds. MiniMax M3.1 Flash brings intelligence and fast, concise responses. SGLang Omni adds streaming, conversation state, and interruption handling so users can redirect conversations in real time. Together, they give developers a foundation to explore proactive tutors, support agents, and hands-free copilots - pairing Flash’s capabilities with infrastructure for continuous interaction. Thanks to the SGLang Omni team for exploring this direction with M3.1 Flash! ✨
Guitar Cat + LLM 「Will @ SGLang Summit in SF」
@GenAI_is_real22h
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. 🔥
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MiniMax (official) retweeted
AI/ML API
@aimlapiOct 19
MiniMax M3.1 Flash mogs Muse and DeepSeek for FREE 🔥 Try Space Bunny on aimlapi.com
MiniMax (official)
@MiniMax_AIOct 19
MiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: platform.minimax.io M Plan: minimax.io/m-plan MiniMax Code for desktop: agent.minimax.io/download
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One model string away: "minimax:m3.1@flash" Thanks @runware for shipping M3.1 Flash so fast 🚀
Runware
@runwareOct 21
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
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MiniMax (official) retweeted
Atomic Agent
@atomicagent_ioOct 20
MiniMax M3.1 Flash got 1.5x faster in Atomic Agent! We ran a Halloween prompt that builds one continuous 3D scene. In Atomic Fusion a local Qwen 3.8 27B wrote the plan, MiniMax did the coding and it was done in 8 minutes! Try Atomic Agent for FREE -> atomicagent.io
MiniMax (official)
@MiniMax_AIOct 19
MiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: platform.minimax.io M Plan: minimax.io/m-plan MiniMax Code for desktop: agent.minimax.io/download
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MiniMax (official) retweeted
Leanna Ren
@RenLeannaOct 20
❤️open weights soon!
Sophia Yang
@sophiamyangOct 19
TL;DR: - MiniMax M3.1 Flash is the anonymous "Space Bunny" model that was #1 on OpenCode for 12 days straight - 1M context, with text, image and video input - 1/3 the cost of M3 and 3x the speed - $0.15 / $0.60 per 1M input/output tokens, cache reads $0.015 - Automation-Bench: 62.2%, ahead of Opus 5 (50.3%) and GPT-5.6 Sol (45.8%) - DeepSWE: 73.7%, about tied with Opus 5 (74.0%) and behind DeepSeek V4.1 Flash (77.0%) - ALE: 29.6% for about $111 total, close to Opus 5 (32.2%) and GPT-5.6 Sol (30.6%); Opus 5.5 scores higher (about 38%) but costs over $1,000 - BabyVision: 91.0%, just behind DeepSeek V4.1 Flash (92.5%) - Open weights coming later, no date yet
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Thank you Parallel Web System to provide such a meaningful data point~ Yes, MiniMax M3.1 Flash is now #1 on search capabilities leaderboard for efficiency. And it's fast~
Parallel Web Systems
@p0Oct 20
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.
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Even the rabbit stopped to watch. 🐰🚀 Love seeing what @higgsfield_ai is creating with MiniMax M3.1 Flash.
Higgsfield AI 🧩
@higgsfield_aiOct 20
MiniMax M3.1 Flash vs Claude Opus 5.5 in cinematic absurdity. Two takes on the impossible, made with Higgsfield.
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MiniMax (official) retweeted
Higgsfield AI 🧩
@higgsfield_aiOct 20
MiniMax M3.1 Flash vs Claude Opus 5.5 in cinematic absurdity. Two takes on the impossible, made with Higgsfield.
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MiniMax (official) retweeted
TokenRouter
@TokenRouter_USOct 19
The 🐰 is out of the bag. It’s MiniMax M3.1 Flash from @MiniMax_AI, and it’s now on TokenRouter. M3.1 Flash scores 73.7% on DeepSWE v1.1, so it can burrow into a real codebase and come back with working fixes. On AutomationBench-AA it reaches 62.2, a test of business workflows that jump across several SaaS tools before the job is done. Output costs $0.60 per million tokens, which is not many carrots for a model this fast on its feet. Let it loose on TokenRouter: tokenrouter.com/models
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⌘ + 🐰 = 🚀 Thanks @CommandCodeAI! M3.1 Flash is free for all subscribers for a limited time.
Command Code
@CommandCodeAIOct 19
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
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MiniMax (official) retweeted
Hassan
@nutlopeOct 19
This model is insane at design. And 88x cheaper than Claude Opus 5.5 on my test! I asked M3.1 Flash (left) and Opus 5.5 (right) to build me a landing page for a hardware device launch. MiniMax cost just $0.014 vs $1.22 for Opus, while being 4x faster and more token efficient.
MiniMax (official)
@MiniMax_AIOct 19
MiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: platform.minimax.io M Plan: minimax.io/m-plan MiniMax Code for desktop: agent.minimax.io/download
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From stealth to production 🐰→🏭 Thanks @gmi_cloud for getting M3.1 Flash live on day0. If you're running agents at scale, this is a great place to run it.
GMI Cloud
@gmi_cloudOct 19
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 👇
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Built for exactly this: long agentic coding runs where cost adds up fast 🐰 Thanks @cline for having M3.1 Flash ready on day0. Free in Cline now, so point it at your gnarliest repo and let it cook.
Cline
@clineOct 19
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!
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Thanks for keeping the secret, @OpenRouter 🤫🐰 And thank you to every dev who kept Space Bunny at #1 for 10 straight days 🏆 You were using the early build. Wait till you try this one: The final M3.1 Flash is live and free on OpenRouter for 72h!
OpenRouter
@OpenRouterOct 19
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.
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12 days at #1 on @opencode, and it was only the early build 🐰🏆 Thank you to every dev who picked an anonymous model and stuck with it. The finished M3.1 Flash is live now, and it's free on OpenCode for 3 days. Go see what changed!
OpenCode
@opencodeOct 19
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
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Day0 support from @ollama 🦙🤝🐰 M3.1 Flash, US-hosted, zero data retention, ready for your agents. Go build!
ollama
@ollamaOct 19
MiniMax M3.1 Flash is on Ollama! 🔒 Hosted in the US and with zero data retention. Fast coding and agentic workflows, with image understanding and a 1M-token context window. Try it on Ollama Cloud: ollama run minimax-m3.1-flash:cloud Claude Code: ollama launch claude --model minimax-m3.1-flash:cloud Codex: ollama launch codex -–model minimax-m3.1-flash:cloud
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