multimodal benchmark
MM-BrowserComp Leaderboard
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.
Updated Aug 17, 2026
Models1
Model coverage1
MetricScore
EvidenceB
MM-BrowserComp Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelXI | Score52.0% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
MM-BrowserComp Highlights
The leading models and scores on this benchmark.
The Top AI Models for MM-BrowserComp
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis mm-browsercomp AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01XIMiMo-V2-OmniXiaomi
- Score
- 52.0%
- Price
- $0.14 input / $0.28 output per 1M tokens
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures MM-BrowserComp, not total model capability
Selection summary
Best AI Models for MM-BrowserComp
MiMo-V2-Omni currently leads MM-BrowserComp with 52.0%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What is MM-BrowserComp?
What MM-BrowserComp measures and how its scores work.
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.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MM-BrowserComp
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- mm-browsercomp|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MM-BrowserComp.
Which model scores highest on MM-BrowserComp?
MiMo-V2-Omni is currently ranked first with 52.0%.
What does MM-BrowserComp measure?
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.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.