Skip to content

Xiaomi Proprietary Released Mar 18, 2026 Updated

MiMo-V2-Omni

ToolsGuide Scores, rankings, test results and price.

Model summary

  • Text #106 / 416

    362 / 1,000

    ToolsGuide Score· votes only

  • Vision #82 / 167

    357 / 1,000

    ToolsGuide Score· votes only

  • Price per 1M tokens

    No listed price

Summary

MiMo-V2-Omni is Xiaomi's model, released Mar 18, 2026. It's ranked in 2 categories and does best at text: #106 of 416, with a ToolsGuide Score of 362 against a median of 235.

It also ranks #82 of 167 for vision (357).

Its text and vision score uses votes only, because it has published fewer than two of the tests used for those categories.

It has published results on 5 tests and has the top score on 1 of them, including MM-BrowserComp.

Specifications

Creator
Xiaomi
Licence
Proprietary
Released
Mar 18, 2026
Context window
–
Input price
–
Output price
–
Tests reported
5
Settings ranked
mimo-v2-omni, MiMo-V2-Omni

Model comparison

Against the ten best text models.

Text score

ToolsGuide Score out of 1,000 · Higher is better

Vision score

ToolsGuide Score out of 1,000 · Higher is better

Input price

USD per 1M input tokens · Lower is better

Leaderboards

Where MiMo-V2-Omni sits among the top 20 in each category.

Text

#106 of 416 · ToolsGuide Score out of 1,000, where 1,000 is a flawless model

Full text leaderboard →

Vision

#82 of 167 · ToolsGuide Score out of 1,000, where 1,000 is a flawless model

Full vision leaderboard →

By task

Scored from votes on each kind of prompt alone, on the same 1,000-point scale.

Against its nearest rivals

Text prompts by kind · ToolsGuide Score from votes · hover for values

Text

mimo-v2-omni · hover a bar for its rank

Vision

MiMo-V2-Omni · hover a bar for its rank

Test results

Every test MiMo-V2-Omni has a published result on, out of 100%, with its rank among the models that took it.

  • SWE-Bench Verified

    #41 / 120

    Fixing real bugs in real GitHub projects, checked by the projects' own tests.

    74.8%

    Self-reported

  • Claw-Eval

    #13 / 14

    Claw-Eval tests real-world agentic task completion across complex multi-step scenarios, evaluating a model's ability to use tools, navigate environments, and complete end-to-end tasks autonomously.

    54.8%

    Self-reported

  • PinchBench

    #4 / 7

    PinchBench evaluates coding agents on real-world agentic coding tasks, measuring both best-case and average performance across complex software engineering scenarios.

    81.2%

    Self-reported

  • OmniGAIA

    #2 / 2

    OmniGAIA evaluates multimodal perception and reasoning in agentic contexts, testing a model's ability to process diverse inputs and perform complex multi-step reasoning tasks.

    49.8%

    Unverified

  • MM-BrowserComp

    #1 / 1

    MM-BrowserComp evaluates multimodal agents on web browsing and information retrieval tasks, testing a model's ability to perceive, navigate, and extract information from real web environments.

    52.0%

    Unverified