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#07A+May 18, 2026Evidence B

MiMo-V2.5

Xiaomi · Undisclosed (MoE)

The breakout of 2026

1M context, omni-modal understanding and the #1 call volume on OpenRouter in July 2026. Improving fast on Chinese and video, but public eval samples remain thin — evidence grade B.

TextImageVideoAudioNative

Last updated Oct 18, 2026Editorial scoring

Bottom line

MiMo-V2.5 is ecosystem-driven: real phone, car and IoT data make it practical for edge multimodal tasks, at half the price of the leaders. The risk is fast version churn and incomplete public benchmarks.

Eight-dimension breakdown

editorial mapping · 0–100
Perception91Document90Chart QA89Video93Agent90Generation86Chinese90Ecosystem888D
  • MiMo-V2.590.1
Visual perception & grounding20%
91
Document parsing & Chinese OCR18%
90
Chart & document reasoning14%
89
Video & long-horizon reasoning14%
93
GUI agents & tool use14%
90
Generation & editing6%
86
Chinese context & culture6%
90
Ecosystem, cost & availability8%
88

Weights: perception 20 / documents 18 / charts 14 / video 14 / agents 14 / generation 6 / Chinese 6 / ecosystem 8. Definitions and sources on the methodology page.

Public benchmarks

as reported, not converted
Benchmark / metricValueNote
OpenRouter 调用量#1July 2026
上下文1MOfficial spec
调用量增长+616%May–Jul 2026

Public scores come from different versions and prompts and are not interchangeable with our composite; they are one evidence input.

Scenario mapping

five stress tests, one scale
ScenarioScoreObservation
Chinese receipt OCR88 · Fine on standard receipts
Chart data extraction88 · Stable on simple charts
30-min video QA93 · Best value for long video
Mobile GUI control89 · Well tuned to own devices
Chinese cultural context89 · Strong everyday scenes; average academic context

Strengths and limitations

Strengths

  • Half the flagship price with standout video value.
  • Rich device/edge data; steadier on real-world photos.
  • 1M context is friendly to long video and many-image inputs.

Limitations

  • Sparse public evaluations; evidence grade capped at B.
  • Enterprise SLAs and on-prem options are still maturing.
  • Complex document layout trails document specialists.

Price and real cost

List price

¥6/M tokens

≈ ¥6 / 1M output tokens. For 1,000 images at 1,024px, ~1,100 image tokens each and 300 output tokens, the monthly cost is about ¥3.6 (assuming input at 25% of output price).

Use your volume

About MiMo-V2.5

Is MiMo-V2.5 open source?

Licence: Closed API + partial open weights. No public weights; access is via vendor API or an on-prem licence.

How much does MiMo-V2.5 cost?

≈ ¥6 / 1M output tokens. It ranks #7 with a composite of 90.1. Real bills depend on resolution, tiling, caching and volume discounts.

What is MiMo-V2.5 best for?

Edge and in-car multimodal interaction; Short-video understanding and tagging; Cost-sensitive batch image tasks。

Why does MiMo-V2.5 score 90.1?

The composite weights eight dimensions: perception 20%, documents 18%, charts 14%, video 14%, agents 14%, generation 6%, Chinese 6%, ecosystem 8%. Its strongest dimension is Video & long-horizon reasoning; its weakest is Generation & editing.

Personal ranking · Not an official score

Every ranking, score and comparison on this page is an independent personal ranking, not an official score, and represents no vendor, institution or regulator. Scores are a subjective mapping of public evidence under our own weights — change the weights and the order changes. Disagree, or spotted a factual error? Contact the site owner: jizhi2024@foxmail.com — we check each report and log corrections in the changelog.