Xiaomi MiMo — Fast Reasoning, Lightweight Deployment, Fully Open Source

Xiaomi MiMo is a reasoning-first LLM family purpose-built for agents, optimized for complex reasoning, high-efficiency coding, long-context understanding, and tool use—moving AI from “answering questions” to “completing tasks.”

MIT License Reasoning-first Human–Car–Home Edge + Cloud MoE Flagship

Download Models Try MiMo Studio

Key Metrics

73.4%

SWE-Bench (MiMo-V2-Flash)

56k

Context Window

150 tok/s

Inference Speed

7B → 309B

Model Span

From MiMo-7B to MiMo-V2-Flash (MoE), Xiaomi MiMo balances big-model performance with small-model efficiency for edge and cloud.

Why Xiaomi MiMo

Xiaomi MiMo tackles the hardest landing problems—high compute cost, slow inference, and weak long-context handling—while powering the Human–Car–Home ecosystem with open, MIT-licensed models.

Efficiency + PerformanceDynamic MoE activation, Hybrid Attention, and multi-layer MTP deliver 2–2.6× faster inference without sacrificing reasoning depth.

Edge-first DNAQuantization (e.g., INT4), pruning, and hardware-aware optimization make Xiaomi MiMo run on phones, cockpits, and smart speakers with low latency.

Open & AccessibleMIT License, Hugging Face distribution, and developer guides reduce friction for teams of any size to adopt Xiaomi MiMo.

Agent-GradeDesigned to sustain hundreds of tool-augmented turns for complex tasks, moving from Q&A to task completion.

Xiaomi MiMo Family

A layered lineup that balances reasoning excellence with deployment flexibility, from lightweight 7B to MoE flagship.

MiMo-7B

7B reasoning-first, math and code strong, lightweight for on-device. Ideal for HyperOS experiences and offline/weak-network use.

ReasoningMathCodeOn-device

MiMo-V2-Flash (MoE)

309B total / 15B active, 56k context, 150 tok/s, SWE-Bench 73.4%. Flagship MoE for long-context, high-speed reasoning and coding.

MoELong contextHigh speed73.4% SWE-Bench

MiMo-VL

Multimodal vision+language branch for perception-rich tasks, powering proactive home orchestration and cross-device experiences.

VisionMultimodalScene understanding

MiMo-Audio

Speech understanding and generation tuned for natural voice assistants across Xiaomi devices, optimized for latency and wake-word accuracy.

SpeechReal-timeWake-word

MiMo-Embodied

Cross-domain embodied intelligence bridging robotics and autonomous driving; built to control, perceive, and act with safety-aware reasoning.

EmbodiedRoboticsAutonomous driving

Xiaomi MiMo Architecture & Methods

MiMo’s technical spine combines MoE, Hybrid Attention, and compression to keep reasoning sharp while enabling edge deployment.

MoE + Dynamic ActivationSelective expert routing balances throughput and quality, keeping active parameters lean (15B active in MiMo-V2-Flash).

Hybrid Attention + MTPMulti-layer MTP and hybrid attention deliver 2–2.6× faster decoding for Xiaomi MiMo without context loss.

Compression & QuantizationINT4-ready, structured sparsity, and device-aware kernels tuned for Xiaomi hardware to drop latency and power.

Training at Scale~2.5T tokens pretraining, reinforcement learning fine-tuning for reasoning and code, ScaledAdam optimizer, GPU clusters + Xiaomi AI chips.

Tool Use & AgentsBuilt-in support for tool calling and multi-turn agent loops, sustaining hundreds of interactions with stable reasoning.

Xiaomi MiMo Deployment: Edge, Cloud, Hybrid

Xiaomi MiMo is engineered to meet users where they are—on-device for privacy and latency, cloud for scale, and hybrid for balance.

On-devicePhones, smart speakers, car cockpits. Offline-ready, low-latency, privacy-first. Ideal for HyperOS and in-cabin agents.

CloudMiMo Studio for online inference, evaluation, and experimentation; fast iteration for global teams.

HybridTask-aware split between edge and cloud to optimize cost/performance; adaptive routing for long-context or heavy reasoning bursts.

Xiaomi MiMo Use Cases — Human · Car · Home

Xiaomi MiMo powers end-to-end experiences across personal devices, vehicles, and smart homes—delivering proactive, context-aware intelligence.

Human (Mobile)

HyperOS integration with Xiaomi MiMo delivers faster responses, robust long-text handling, code reasoning, and multi-turn instructions entirely on-device or hybrid for resilience.

Car

In-cabin assistants leverage Xiaomi MiMo for navigation, entertainment, vehicle control, and safety-aware reasoning—edge-optimized for real-time voice and multi-turn dialogue.

Home

Xiaomi Miloco (MiMo-VL-Miloco) orchestrates proactive scenes; MiDashengLM-7B powers voice control as an IoT hub to manage billions of connected devices with scene automation.

Xiaomi MiMo Benchmarks & Proof

Xiaomi MiMo closes the gap with frontier models while staying deployable on everyday hardware.

73.4%

SWE-Bench (MiMo-V2-Flash)

56k

Context window

150 tok/s

Inference speed

7B–309B

Model range

MiMo-7B: reasoning-first, math/code-strong, on-device optimized (official MMLU/HellaSwag pending). MiMo-V2-Flash: MoE flagship with long context and speed. Strategy: big-model performance + small-model efficiency.

Xiaomi MiMo Roadmap & Milestones

Xiaomi MiMo is iterating from single reasoning to multimodal, audio, and embodied intelligence.

2025-04-30MiMo-7B open sourced (reasoning-first 7B).

2025-11-21MiMo-Embodied open sourced (cross-domain embodied intelligence).

2025-12-16/17MiMo-V2-Flash released & open sourced (MoE flagship, 56k context, 150 tok/s).

ContinuousExpansion to multimodal, audio, embodied; ongoing optimization for edge + cloud.

Xiaomi MiMo Developer Resources

Everything you need to adopt Xiaomi MiMo: code, weights, guides, and community.

Open Source (MIT)Weights and code on Hugging Face and GitHub for Xiaomi MiMo models; clear licensing for commercial use.

QuickstartInference snippets, tool-use examples, long-context prompts, and agent templates to ship faster.

Fine-tuning & INT4Guides for domain fine-tune, INT4/on-device deployment, and hybrid edge/cloud recipes.

CommunityIssues, discussions, contribution guide; feedback loop with Xiaomi MiMo Core Team and AI Lab.

Xiaomi MiMo Team, Trust, and Ecosystem

Built by Xiaomi LLM Core Team, AI Lab, and hardware adaptation teams, led by Luo Fuling—backed by ¥40B AI investment and a global device footprint.

StakeholdersXiaomi Group, hardware divisions, developer community, Hugging Face platform.

PartnersSemiconductor partners and GPU vendors powering MiMo training and inference; Xiaomi hardware ecosystem for deployment.

Ecosystem ValueDifferentiates Xiaomi phones, cars, and smart home; raises user experience across Human–Car–Home.

Xiaomi MiMo Transparency & Open Questions

Xiaomi MiMo shares progress openly and highlights areas still evolving.

Pending BenchmarksOfficial MMLU/HellaSwag for MiMo-7B are not yet disclosed.

Quantization DetailsFurther guidance on MiMo-V2-Flash edge quantization and recommended accelerators will be published.

Training DataFull dataset composition and cost breakdown remain internal; Xiaomi MiMo is iterating responsibly.

B2B PathExternal enterprise cases are in exploration; Xiaomi will package mature solutions for targeted industries.

Xiaomi MiMo Future Outlook

Xiaomi MiMo continues to evolve: deeper Human–Car–Home fusion, stronger multimodal and embodied intelligence, and broader developer enablement.

Human–Car–Home 2.0Next-gen phones, richer cockpits, and whole-home AI orchestration powered by Xiaomi MiMo.

MoE EvolutionSmaller active params with larger total capacity to lower edge thresholds while boosting reasoning quality.

Multimodal DepthVideo understanding, perception-action loops, and embodied control for robotics and autonomous driving.

Enable OthersDeveloper programs, cloud APIs, and app ecosystem to let partners build with Xiaomi MiMo quickly.

Xiaomi MiMo FAQ

Is Xiaomi MiMo open source?

Yes. Xiaomi MiMo models are released under the MIT License, with weights and tooling available for global developers.

Can I deploy Xiaomi MiMo on device?

Yes. Xiaomi MiMo is optimized for lightweight, low-latency edge deployment on phones, smart speakers, and car cockpits, with INT4/quantization support.

What is the flagship Xiaomi MiMo model?

MiMo-V2-Flash is the MoE flagship with 56k context, 150 tok/s inference, and 73.4% SWE-Bench performance.

What are the main use cases?

Human–Car–Home: HyperOS assistants on-device; in-car voice and multi-turn agents; proactive smart home with Xiaomi Miloco and MiDashengLM-7B IoT control.

Where can I get the models?

Weights and code are available on Hugging Face and GitHub under the MIT License; MiMo Studio offers cloud access for evaluation.

Build with Xiaomi MiMo

Download the Xiaomi MiMo models, explore MiMo Studio, or talk with our team about deployment across Human–Car–Home.

Download Models Contact Team