The model weights are completely free under the MIT open-source license, so you can download and self-host them. The cloud API is pay-per-token, with monthly Token Plan subscriptions and free-token developer incentive programs also available.

How much does Xiaomi MiMo-V2.5 cost?

API pricing for MiMo-V2.5-Pro is about $1.00 per million input tokens and $3.00 per million output tokens (0-256k context), doubling for the 256k-1M window. The omnimodal MiMo-V2.5 is cheaper at about $0.40 input / $2.00 output.

Is Xiaomi MiMo better than DeepSeek?

MiMo wins on long-horizon agent tasks, token efficiency (40-60% fewer tokens), and native multimodal understanding. DeepSeek V4 is stronger at deep reasoning and complex coding quality. Use DeepSeek for quick high-quality code, MiMo for cost-effective agent workloads.

Is Xiaomi MiMo open source? Can I use it commercially?

Yes. MiMo-V2.5-Pro and MiMo-V2.5 are released under the MIT license, allowing free commercial use, fine-tuning, and further training.

Does Xiaomi MiMo work with Claude Code?

Yes. Reviewers rate it among the best models for use with Claude Code in China. In tests it built a full data-analysis platform in one pass and fixed bugs that Claude Opus 4.6 had left behind.

What are the main drawbacks of Xiaomi MiMo?

The main weaknesses are weak frontend design/aesthetics, average live web-search ability, a tendency to take the shortest path in coding (quality sometimes below DeepSeek V4), and not proactively invoking advanced installed skills.

ring: Xiaomi MiMo Review 2026: MiMo-V2.5-Pro Features, Pricing, Pros & Cons

Xiaomi MiMo Review 2026: MiMo-V2.5-Pro Features, Pricing, Pros & Cons

August 6, 2026 · Updated 2026 · AI Tools · Read time: ~8 min

Verdict first: Xiaomi's MiMo-V2.5-Pro is a free, MIT-licensed, 1-trillion-parameter open model built for AI agents — with the best token efficiency on the market. Developers should absolutely try it; casual users should wait for the consumer apps.

Xiaomi MiMo — the open-source AI model series built for agents

What Is Xiaomi MiMo?

Xiaomi MiMo is the self-developed large language model series from Xiaomi, led by Luo Fuli (a former core member of DeepSeek). It's positioned as an AI-agent-first model and serves as the AI backbone for Xiaomi's "people-car-home" ecosystem — XiaoAI assistant, smart home, and Xiaomi EV.

On April 23, 2026, Xiaomi launched the MiMo-V2.5 series with four models:

MiMo-V2.5-Pro — flagship, 1T-parameter MoE, built for complex long-horizon agent tasks
MiMo-V2.5 — native omnimodal model (image, audio, video input)
MiMo-V2.5-TTS — speech synthesis
MiMo-V2.5-ASR — speech recognition

On April 28, MiMo-V2.5-Pro and MiMo-V2.5 were open-sourced under the MIT license — free for commercial use, fine-tuning, and retraining. It's one of the biggest open-source releases in Chinese AI, and a serious statement from Xiaomi.

Key Features

1. 1M-Token Context Window

The entire MiMo-V2.5 family supports a 1-million-token context (about 750,000 words) — enough to read dozens of papers, an entire novel, or a full code repository in one pass.

2. 1.02T-Parameter MoE Architecture (V2.5-Pro)

1.02 trillion total parameters, only 42B active per inference — big capability without the cost
Hybrid attention: sliding-window + global attention (6:1 ratio)
FP8 mixed precision, trained on 27 trillion tokens

3. Native Omnimodal Understanding (V2.5)

The standard V2.5 processes images, audio, and video simultaneously:

Reads hospital lab reports and gives conclusions
Understands audio over 10 hours long — audio capability exceeds Gemini 3 Pro
Image understanding surpasses Claude Opus 4.6

4. Long-Horizon Agent Ability ★ Core selling point

MiMo is built for AI agents and can reliably execute nearly a thousand tool calls in a single run:

Official demo: completed a full SysY compiler in Rust (a Peking University course project that takes undergrads weeks) in 4.3 hours with 672 tool calls — scored 233/233
Built an 8,192-line video-editor web app in 11.5 hours (1,868 tool calls)
Designed a graduate-level analog circuit via closed-loop simulation in ~1 hour

5. Token Efficiency (Money Saver)

This is MiMo's standout differentiator:

Uses 40–60% fewer tokens than Claude Opus 4.6, Gemini 3.1 Pro, and GPT-5.4 for the same task
42% fewer tokens than Kimi K2.6 at equivalent benchmark scores
~50% fewer tokens than Meta's Muse Spark

6. MiMo Claw (Lobster) Agent

A separate agent product in public beta:

Financial analysis: accurately parsed a 28-page Apple English financial report into five key conclusions
PPT overhaul: with Kingsoft partnership, upgraded dated course slides to near-Keynote quality

7. UltraSpeed Mode (June 2026)

Using FP4 experts and DFlash decoding, MiMo-V2.5-Pro-UltraSpeed reaches 1,000 tokens/s on general GPUs — ideal for high-concurrency real-time workloads.

Pricing: API & Token Plan (2026)

Model	Input / Million tokens	Output / Million tokens	Notes
MiMo-V2.5-Pro	¥7 ≈ $1.00	¥21 ≈ $3.00	0–256k context
MiMo-V2.5-Pro	¥14 ≈ $2.00	¥42 ≈ $6.00	256k–1M context
MiMo-V2.5	¥2.8 ≈ $0.40	¥14 ≈ $2.00	Omnimodal

Xiaomi MiMo API pricing comparison table per million tokens

MiMo-V2.5 API pricing (per million tokens)

Subscription & free options:

Token Plan: Lite / Standard / Pro / Max monthly tiers, with night discounts, auto-renewal, and annual plans
Developer incentive: a "100-trillion-token creator program" gives away free tokens — testers reported claiming up to 1.6 billion tokens
Open source: model weights are MIT-licensed and free to self-host, ideal for data-sensitive enterprises

What We Liked (Test Results)

✅ Top-Tier Coding & Agent Ability in China

Tested alongside Claude Code, MiMo-V2.5-Pro:

Built a WeChat article data-analysis platform in one pass — Feishu database, internal deployment, unified login, zero revisions
Fixed bugs that Claude Opus 4.6 had left behind
Analyzed a 1.6-million-character novel into an interactive character-relationship webpage

Multiple reviewers call it "one of the best models for Claude Code in China" — with a feel of Opus 4.6.

✅ Solid Logical Reasoning

Passed the classic trap question "should you walk or drive to the car wash?" — correctly identifying that the car you're washing has to be driven there.

✅ Outstanding Multimodal Ability

Audio understanding over 10 hours, accurate identification of blurry product photos, and image understanding beyond Claude Opus 4.6.

✅ Genuinely Useful 1M Context

In real tests, it consumed a 1.6M-character novel and produced full-book analysis — a valuable capability for research, legal, and finance work.

✅ Open Source & Cheap

MIT license plus aggressive token efficiency means dramatically lower total cost than the frontier closed models.

What We Didn't Like

❌ Weak Frontend Design

Generated pages work but lack polish — "usable but not designed." Building websites requires pairing it with a frontend design Skill. This was a consensus across reviewers.

❌ Average Live Web Search

In tests, it made mistakes listing Xiaomi's own phone models (mixing in previous-generation models, missing the new series, misled by a wrong blog). Don't rely on it for up-to-the-minute facts.

❌ Coding Takes the Shortest Path

One reviewer found it leans toward the simplest solution ("it runs, good enough"). All four full-stack test projects ran, but code quality was "hard to praise" — overall coding ability below DeepSeek V4.

❌ Doesn't Proactively Use Advanced Tools

In Claude Code, it won't automatically invoke installed skills like Firecrawl or Context7 unless explicitly told to.

❌ Tool-Call Planning Not Always Smart

It prefers short paths and won't spin up sub-agents for parallel development — long-horizon planning trails the top closed models.

MiMo vs DeepSeek vs Claude (2026 Comparison)

Dimension	Xiaomi MiMo	DeepSeek	Claude Opus 4.6
Open source	✅ MIT	✅	❌
Context window	1M tokens	128K	200K
Coding	Strong (SWE-bench 57.2)	Excellent (V4)	Top tier
Token efficiency	⭐ Best (40–60% fewer)	High	Average
Multimodal	✅ Native omnimodal	Text-focused	✅
API price (input/M)	~$1.00	Very low	High
Standout	1,000 tokens/s UltraSpeed	Reasoning king	All-rounder

How to choose:

Budget agent development → Xiaomi MiMo (cheapest per completed task)
Deep reasoning & complex coding → DeepSeek V4
Absolute capability ceiling → Claude Opus
Very long documents → MiMo / Kimi

Who Should Use Xiaomi MiMo?

✅ Good fit

Agent & automation developers: stable execution of ~1,000 tool calls per run, works with Claude Code / OpenCode / Kilo
Budget-conscious teams: token efficiency + low API price make large-scale workloads affordable
Enterprises needing self-hosting: MIT license keeps data on-premise
Multimodal users: image, audio, and video in one model
Research / legal / finance: 1M context for long documents

❌ Poor fit

Heavy frontend work: design and UI generation are weak; needs extra skills to compensate
Real-time information needs: live web search is average
Maximum code quality: overall coding depth is below DeepSeek V4
Non-technical users: currently developer-focused, with no mass-market consumer app yet

Final Verdict: Is Xiaomi MiMo Worth It?

Developers: absolutely try it. Casual users: wait.

If you're an agent developer or programmer, MiMo-V2.5-Pro's token efficiency and Claude Code pairing are worth using today — and it's free and fully open source.
If you're building multimodal applications, MiMo-V2.5's native omnimodal support at a low price is a strong pick.
If you just want daily Q&A, there's no consumer product yet — wait for it to arrive inside XiaoAI.

MiMo's core strengths: open source, cheap, token-efficient, 1M context, strong agent ability. Its weaknesses: frontend aesthetics, live search, complex coding depth. It's not an all-rounder — but as the "cost-performance pick of the agent era," it has firmly arrived.

Scorecard: Overall 8.0/10 · Agent Ability 9.0 · Token Efficiency 9.5 · Multimodal 8.5 · Value 9.0 · Frontend Design 5.5 · Live Search 6.0

Frequently Asked Questions

1. Is Xiaomi MiMo free?

The model weights are completely free (MIT license) for self-hosting. The cloud API is pay-per-token, with Token Plan subscriptions and free-token developer incentives.

2. How much does MiMo-V2.5 cost?

V2.5-Pro: ~$1.00 input / ~$3.00 output per million tokens (0–256k context), doubling for the 256k–1M window. The omnimodal V2.5 is cheaper at ~$0.40 / ~$2.00.

3. Is MiMo better than DeepSeek?

MiMo wins on agent long-tasks, token efficiency, and multimodal. DeepSeek V4 wins on deep reasoning and complex code quality. Use DeepSeek for quick high-quality code, MiMo for budget agent workloads.

4. Is MiMo open source? Commercial use?

Yes — MiMo-V2.5-Pro and MiMo-V2.5 are MIT-licensed: free commercial use, fine-tuning, and retraining.

5. Does MiMo support Chinese and English?

Both, with balanced ability — well suited for Chinese developers and international workflows.

6. What are MiMo's main drawbacks?

Weak frontend design, average live web search, coding that favors the shortest path (quality below DeepSeek V4), and it won't proactively use advanced installed skills.

If you found this Xiaomi MiMo review useful, check out our other hands-on AI reviews:

Replace each YOUR-XXX-REVIEW-URL with the real post URL, or delete the line if that review isn't published yet.

Disclaimer: This article is based on public information and hands-on media tests from April–August 2026. Pricing and features may change; always confirm with the official source. This content is provided for information purposes only and does not constitute a purchase recommendation.

2026年8月6日星期四