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Move over, Claude and ChatGPT: This Android brand’s open-source AI model builds 3D games on demand

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Why This Matters

Xiaomi is expanding beyond phones and EVs into cutting-edge AI, open-sourcing an omnimodal model, MiMo-V2.6, that claims to be the top-ranked open-weight system on a major intelligence benchmark. Its ability to generate interactive 3D worlds and control robotics from text or images signals growing competition with US labs like OpenAI and Anthropic, and could accelerate open AI innovation industry-wide.

Key Takeaways

Aamir Siddiqui / Android Authority

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TL;DR Xiaomi has open-sourced its omnimodal AI model capable of generating interactive 3D worlds, such as games, from text or visual prompts.

Xiaomi’s MiMO-V2.6 Pro is claimed to be the most capable open-weight model on the Artificial Analysis Intelligence Index benchmark.

Along with open-sourcing it, Xiaomi is widely releasing desktop apps for Windows and Mac.

Smartphones and tablets are likely to come to mind when you first think of Xiaomi. If you’re savvy enough, you might as well know about the company’s diverse portfolio of home appliances and its recent ventures into the EV space. But it might surprise you to learn that Xiaomi is also developing its own frontier AI models to take on the likes of DeepSeek, Claude, ChatGPT, Gemini, and the others.

Xiaomi has just released the latest version of its omnimodal AI models — MiMo-V2.6 Pro and MiMo-V2.6-Flash. These models can be used for textual, visual, and video-based applications, as well as for coding. While the MiMo-V2.6 Pro is Xiaomi’s most capable model, Flash is designed for lower costs and swift responses.

As per Xiaomi, MiMo-V2.6 Pro is the highest-ranking open-source model on the Artificial Analysis Intelligence Index benchmark. It is placed ahead of Qwen3.8 Max and is only slightly behind Claude Opus 5, GPT-5.6 Sol, and Meta Muse Spark, all of which were tested for max effort.

AAI Index

In addition to its open-weights development, Xiaomi is also open-sourcing 7,000+ reinforcement learning (RL) environments as well as the end-to-end RL framework.

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