[whatmodel.sh](../../README.md) / MiMo-V2-Omni # MiMo-V2-Omni Xiaomi · released 2026-03 · closed weights **score 67.2** ±1.7 · comparison only: no current run option verified · from 6 benchmark results across 4 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at _{● marks MiMo-V2-Omni among every model on that task or test, worst to best.}

task                vs the others         rank  counts  tests
chat & writing      ▁▁▁▃▅▄▇█▇●▇▃   #91 of 474*     31%      1
vision & documents  ▁▁▂▃▂▃▅▄▆●█▄    #79 of 189     67%      4

chat & writing · #91 of 474 · 31% of its score

Beats [Claude Haiku 5.5](claude-haiku-5-5.md), [LongCat 2.0 (1.6T-A48B)](longcat-2-0.md), [Muse Glimmer 30B](muse-glimmer-30b.md) here, though they rank higher overall. Trails [Gemma 4 12B](gemma-4-12b.md), [Gemma 4 26B-A4B](gemma-4-26b-a4b.md), [Nemotron Cascade 2 30B-A3B](nemotron-cascade-2-30b-a3b.md) here, though they rank lower overall.

test            result  vs the others in its run    difficulty  counts  why
LMArena (text)  1430.7  ▁▁▁▂▃▃▃▆▆●█▃ beats 287/385  avg 1260       31%  blunt

vision & documents · #79 of 189 · 67% of its score

Beats [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md), [GPT-5](gpt-5.md), [o3](o3.md) here, though they rank higher overall. Trails [Gemma 4 26B-A4B](gemma-4-26b-a4b.md), [Claude Haiku 4.5](claude-haiku-4-5.md), [Qwen3.6 Flash](qwen3-6-flash.md) here, though they rank lower overall.

test                                result  vs the others in its run   difficulty        counts  why
CharXiv (reasoning questions) (ma…   80.1%  ▂▅▃▅▅▆▆▅▆●▆▂ beats 77/101  medium · avg 44%     21%  small run · several runs
Arena vision (style controlled)     1215.9  ▁▁▂▂▂▂▃▄▅●█▇ beats 83/152  avg 1061             21%  blunt
ChartArena chart parsing (English…   43.9%  ▁·▁·▃▃▁▇▃●·▄ beats 15/22   hard · avg 27%       17%  blunt · at its level
MMMU Pro (maker)                     76.8%  ▂▃▁▃▆▇▃▇▇█●▅ beats 43/52   medium · avg 48%    8.4%  at its level · small run

other tests (3)

test                  result  vs the others in its run  counts  why
HR-Bench 4K (maker)    83.3%  ●··········█ beats 0/1         —  not counted yet: no other model in the …
Daily-Omni (maker)     80.5%  ●··········█ beats 0/1         —  not counted yet: no other model in the …
Video-Holmes (maker)   59.5%  ●··········█ beats 0/1         —  not counted yet: no other model in the …

## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md)

source                                    results  share of the score
LMArena leaderboard dataset                     2   52% ▇▇▇▇▇▇
XiaomiMiMo/MiMo-V2.5 model card (submit…        2   19% ▇▇
ChartArena: Benchmarking Chart Parsing …        1   17% ▇▇
Xiaomi MiMo vendor-reported benchmark s…        1   11% ▇
prior: pull toward the middle                        1% ▇
weighted average                                   = 67.2

_{Licences: LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · XiaomiMiMo/MiMo-V2.5 model card ([MIT](../../licenses/XiaomiMiMo--MiMo-V2.5.txt)) · ChartArena: Benchmarking Chart Parsing across Languages ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/))}

Not counted (3)

source                  test          score  why
XiaomiMiMo/MiMo-V2.5 …  HR-Bench 4K   83.3%  too few models have it yet
XiaomiMiMo/MiMo-V2.5 …  Daily-Omni    80.5%  too few models have it yet
XiaomiMiMo/MiMo-V2.5 …  Video-Holmes  59.5%  too few models have it yet

## How to run it No verified API or local download yet. [interactive version](https://whatmodel.sh/model/mimo-v2-omni) · [JSON](https://whatmodel.sh/api?format=json&all=1)