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Introducing Xiaomi MiMo-V2.6 — Pro & Flash.

Frontier intelligence, all the modalities, built in public.

🔹 Two omnimodal models, advancing through scaled reinforcement learning
🔹 Pro performs on par with Claude Opus 5 and GPT-5.6 Sol across most agent benchmarks
🔹 Pro scores 46 ois Intelligence Index — the highest among open-source models
🔹 Stronger coding, computer use, 3D reasoning and creative capabilities
🔹 Open model weights, technical report, RL environments and training code

Blog:mimo.xiaomi.com/mimo-v2-6
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MiMo V2.6 Pro ranks #1 on the Agent Arena open-model leaderboard, while both Pro and Flash land on the performance-cost Pareto frontier. 🚀
Exciting update: There’s a new leader in the Agent Arena among open models. MiMo V2.6 Pro by @XiaomiMiMo has landed the #1 spot with +3.8% net improvement!

Earlier this week we evolved the Bash Recovery signal in Agent Arena (more info in thread). With this update, the new top 5 iMo V2.6 Pro: +3.8%
- #2 Deepseek V4.1 Flash (Max): +3.0%
- #3 Hy4 preview: +2.9%
- #4 MiMo V2.6 Flash: +2.5%
- #5 GLM 5.2 (Max): +2.4%

MiMo V2.6 Pro ($0.11 cost per task) and Flash ($0.05 cost per task) are the only two open models on the Agent Arena Pareto frontier!
- Pro outperforms both #2 Deepseek V4.1 Flash while costing 15% less, and #3 Hy4 preview while costing 71% less.
- Flash is 1.3 percentage points below Pro but is 55% cheaper.

Congrats to the @XiaomiMiMo team on this contribution to the open ecosystem!
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🎉 MiMo-V2.6-Pro leads the open-weight field on FrontierCode 1.1 at 45%.
We're launching our leaderboard for FrontierCode 1.1, a private evaluation from Cognition that tests models on completing coding tasks in a way that would actually get merged by maintainers of real-world repositories

@cognition announced FrontierCode in June 2026 and updated it Cognition built the dataset with open source maintainers who spent more than 40 hours per task. Each task requires the agent to make a change to a real open source repository, then checks both unit tests and qualitative tests for what maintainers would require to merge the change.

We run FrontierCode 1.1 Main, the primary 100-task set of the benchmark's 150 tasks, using our Stirrup open source reference harness for apples-to-apples comparisons across models. All tasks are private to avoid contamination. Each attempt is graded with both blocking and non-blocking criteria. An attempt that fails any blocking check scores zero, and one that passes them all scores between 70% and 100%.

Unlike other coding evaluations, FrontierCode has a more holistic view of success based on real usage. Models need to pass unit tests, but are also assessed on behaviors like making excessive changes and large diffs, modifying files outside the relevant scope, or adding unhelpful tests. We think this approach is valuable in the current context: models are now very capable at coding tasks, but their changes can still require substantial cleanup before a maintainer would merge them.

Key takeaways:

➤ Leading models still fail more than 40% of the time: Claude Opus 5.5 (max with fallback) leads at a score of 52% after passing blockers in 58% of its attempts. Nine of the 100 tasks were not passed in any attempt by any of the models we evaluated for launch

➤ The top of the leaderboard is tightly packed: nine models from six labs score between 43% and 52%. MiMo-V2.6-Pro is the leading open weights model at 45%, followed by DeepSeek V4.1 Flash (max) and Kimi K3 (max) at 44%

➤ GPT-6.1 Sol (max) offers the strongest performance for its cost: At $0.81 per task it scores 49%, matching Claude Fable 5.1 (max with fallback). This means it achieves similar performance to leading Anthropic models, at less than a tenth of the cost per task

Thank you to @silasalberti, @ybenpan, @cl571128, and the rest of the team at Cognition for building FrontierCode and collaborating with us to bring it to Artificial Analysis - we’re working to add FrontierCode to our coding agent leaderboard very soon.
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💗
BREAKING: MiMo-V2.6-Pro by @XiaomiMiMo lands at #8 overall (#3 open-weight) on Design Arena with an Elo of 1338.

This is an impressive 54-point and 22-position increase from MiMo-V2.5-Pro.

MiMo-V2.6-Pro also reaches #4 overall in Website (#2 open-weight) and #6 overall in pment (#2 open-weight), showing strong performance across both direct generation and agentic coding.

This places @XiaomiMiMo's new model among leading models such as GPT-5.6 Sol by @OpenAI, Claude Opus 5 by @Anthropic, and Kimi K3 by @MoonshotAI.

Congratulations to the @XiaomiMiMo team on returning to a top-10 placement on Design Arena!
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MiMo-V2.6-Pro just landed @XiaomiMiMo back in the top 10 on Code Arena: WebDev, debuting at ~#10 overall, and ~#3 among open-weights models with an MIT license.

It scores 1628 pts (AutoEval), tying Claude Fable 5 (High) and just ahead of Hy4-preview (1624 pts).

That's a +153 pt MiMo-V2.5-Pro (1475 → 1628 pts).

Among open-weights models, it lands at ~#3. Impressively only 7 pts behind Qwen3.8 Flash Next (#2) and 46 pts behind Kimi K3 Max (#1).

Note: this is an early AutoEval score, in which a Reward Model trained on Arena’s human preference data casts automatic votes in place of live votes. We’ll continue to see how scores converge as more live human votes come in.

Congrats to the @XiaomiMiMo team on this release!
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Replying to @XiaomiMiMo
We’re open-sourcing Pro and Flash, MiMo-V2.6-Distill-Qwen-9B, the technical report, 7K+ RL task environments, an end-to-end RL framework and composable mini-harnesses.
Reproduce, verify and build on the work.
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Replying to @XiaomiMiMo
Start building with MiMo-V2.6. 🚀

MiMo Desktop and membership plans launch alongside Pro and Flash. Use both models with a subscription, or bring your own API key.

MiMo-V2.6-Pro UltraSpeed is now available in Desktop and through the API, delivering up to 20× faster generation for workflows where response time matters.

API pricing remains unchanged from V2.5.

💻 Desktop: mimo-ai.xiaomimimo.com/desktop/
🔗 API: platform.xiaomimimo.com
🤗HF: huggingface.co/collections/Xi…
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Before you meet MiMo-V2.6, step into its world.

Every 3D model, game, slides, video, music and image in MiMo Gallery was generated by MiMo-V2.6.

Stay for the piano. Play a game. Catch the fireworks.

A first look at what's coming: mimo.xiaomi.com/mimo-gallery/
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Xiaomi MiMo Desktop is now in invite-only beta!
🚀 Xiaomi MiMo Desktop is now in invite-only beta.

Invitees also get free, limited access to next-gen MiMo models during the beta.

MiMo Desktop is a desktop agent — not another chat window. It takes your raw materials — Office files, images, video, audio, even zips — lans the path, and ships finished, editable output.

What it can do:
🔹 Previews you can touch. Games, dashboards, demos load live in-session — click, break, and keep iterating. No local frontend setup required.
🔹 Edit by selection. Click or box-select any region — describe the change, and only that part updates. Every revision is versioned, so you can roll back anytime.
🔹 Smart dispatch. The system routes tasks to the right model and agents for you — quality when it matters, speed when it doesn’t. No model-menu guesswork.
🔹 Browser & computer use. It drives your browser to research, fill forms, and extract assets, then feeds findings straight into the task. Full computer use — screen, keyboard, mouse, cross-app work — with record & replay for repeatable flows.
🔹 Long tasks stay affordable. Partial regeneration + cache hit rates up to 99% in-session.

Seats are limited. Apply here: mimo-ai.xiaomimimo.com/desktop/invite/
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Open-weights are taking over — proud to see more developers building on MiMo. 👏 @cline
We’ve been impressed with GLM-5.2 and so are introducing a $9.99/month subscription to give you 2-5x discounted access to it and other open weight models like DeepSeek, Kimi, MiniMax, Mimo, Qwen.

Use it on Cline CLI & IDE with $1.99 special promo if sign up via: npm i -g cline
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Xiaomi MiMo retweeted
MiMo-V2.5-Pro-UltraSpeed Beta Access Extended

Driven by overwhelming developer demand, we’ve extended the UltraSpeed trial window to unlock 1,000 tokens/s ultra-low-latency inference for more builders.

Key traction as of June 23(UTC+8):
• 📈 66,000+ applications submitted
• 🌐 Users spanning Fortune 500s, industry leaders, independent developers & academia
• 🚀 Coverage across finance, legal, telecom, logistics, automotive, media and research

Applications remain open, and approved users keep their access. We'll give advance notice before access closes, with time to migrate.

Access:
• 📝 Apply: platform.xiaomimimo.com/ultraspeed
• ⚙️ API — limited-time pricing (3× MiMo-V2.5-Pro), ~10× faster output: mimo.mi.com/models/zh-CN/m…
• 💬 Chat — free for approved users: ultraspeed.xiaomimimo.com

Commercial or large-scale use: 📮business-mimo@xiaomi.com
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🚀 MiMo Claw is now live!
🚀 MiMo Claw is LIVE
Flagship AI Model + Kingsoft Office Integration

🤖 Unlock the Full Power of Agents
• Powered by MiMo’s flagship model for reliable long-running tasks
• 40–60% lower token consumption than comparable solutions, delivering better long-term value

📄 e Place
• Supports Word, Excel, PowerPoint, and PDF workflows
• Generate professional documents, spreadsheets, and presentations with built-in templates

🎁 Expanded Free Benefits
• Free to get started
• Daily usage expanded from 1 hour to 4 hours
• Fully cloud-based with zero deployment required

💰 Limited-time subscription: ¥14.9/month

👉 Try Now: aistudio.xiaomimimo.com/#/
👉 Subscribe: platform.xiaomimimo.com/token-plan
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🚀 MiMo Code V0.1 is now live and open-source!

More than an AI coding assistant in your terminal — it's the smartest coding partner you'll ever work with.

Comes with MiMo V2.5, a multimodal model available free for a limited time, featuring a million-token context window—ready ♾️ Infinite Context: Knowledge accumulates automatically, and with lossless compression, even million-line projects keep every critical detail intact—quality never drops.
🧠 Agent-Model Synergy: An Agent framework deeply optimized for MiMo, with a full closed loop of testing, review, and validation—so complex tasks get done in one pass.
📝 Compose Mode: Specs → Plans → Build → Report. Design first, code second—clear thinking, no rework.
🔄 Self-Evolving System: Every session is automatically reviewed, distilling experience and best practices—the more you use it, the smarter it gets.
🎙️ Voice Input: Powered by MiMo-V2.5-ASR — just speak instead of type, and your voice becomes the prompt for truly hands-free coding.
🔌 Claude Code Compatible: Automatically loads your existing skills, MCP servers and commands, and reuses your API configuration—zero-cost migration, no setup required.
🌐 Open & Flexible: MIT licensed, with support for leading model providers including Anthropic, OpenAI, DeepSeek, Kimi, GLM and more.

Install in one line:
Mac & Linux
curl -fsSL mimo.xiaomi.com/install | bash
(For the best experience,we recommand Mac user use it on iTerm or vscode terminal)
Windows
npm install -g @mimo-ai/cli

🔗 Learn more
Website ↓
mimo.xiaomi.com/mimocode
Blog ↓
mimo.xiaomi.com/zh/blog/mimo-c…
GitHub ↓
github.com/XiaomiMiMo/MiM…
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1,000+ tokens/s is fast. 🚀
But what does that actually unlock?
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🚀 1,000+ TOKENS/S ON A 1T MODEL! 🚀

We are thrilled to release Xiaomi MiMo-V2.5-Pro-UltraSpeed in collaboration with @TileRT_AI , breaking the 1,000 tokens/s output speed on a 1 Trillion parameter model for the FIRST TIME!

Not wafer-scale integration like Cerebras. Not pure Groq. We achieve 1,000 tps on a 1T MoE model using just a SINGLE, STANDARD 8-GPGPU NODE.

Read the full technical deep dive:mimo.xiaomi.com/blog/mimo-tile…

Want to experience the future of real-time AI?
👉 Apply for UltraSpeed now: platform.xiaomimimo.com/ultraspeed
⏳ Limited-Time Access: Application-based · Jun 8 – Jun 23 (PDT)
💬 Chat Experience: Completely FREE for a limited time — try the blazing-fast web chat now.
⚡ UltraSpeed API: Just 3x the price for a ~10x boost in output experience.
🤝 Enterprise & Large-Scale Needs: business-mimo@xiaomi.com
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Replying to @XiaomiMiMo
🔓 And the best part — we're open-sourcing it.

1,000+ tps on a 1T model wasn't a single breakthrough — it's deep model × system co-design between the MiMo and TileRT teams, all on general-purpose GPUs (no Cerebras-style wafer-scale, no Groq-style SRAM ASICs).
On the model side: FP4 quantization (smaller footprint, less memory traffic) + DFlash, our block-masked parallel speculative decoding that accepts far more tokens per verification. On the system side, TileRT tailors its compiler & kernels to exactly these techniques.

The result: a 1T model breaking 1,000 tps on a single, standard 8-GPU node.

🤗 Open weights (FP4 + DFlash checkpoint): huggingface.co/XiaomiMiMo/MiM…
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