llmboard.ai
Benchmarks
CompareRankings
llmboard.ai
Benchmarks
CompareRankings
HomeBenchmarksmultimodalMobileWorld

multimodal benchmark

MobileWorld

MobileWorld is a benchmark for evaluating multimodal agents on real mobile-device tasks, testing GUI grounding, navigation, and multi-step task completion in mobile environments.

Updated Aug 11, 2026

Models3
Model coverage3
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

MobileWorld Ranking

Higher score ranks better on this benchmark.

3 rows
Columns

Show columns

1ACQwen3.8 MaxAlibaba Cloud / Qwen Team77.8%100.0%3CAug 11, 2026
2BYSeed 2.1 ProByteDance73.1%50.0%3CAug 11, 2026
3BYSeed 2.1 TurboByteDance70.0%0.0%3CAug 11, 2026

MobileWorld Score Distribution

A closer view of the leading scores on this benchmark.

MobileWorld

MobileWorld Highlights

The leading models and scores on this benchmark.

Rank #1Qwen3.8 Max77.8%Rank #2Seed 2.1 Pro73.1%Rank #3Seed 2.1 Turbo70.0%

What is MobileWorld?

What MobileWorld measures and how its scores work.

MobileWorld is a benchmark for evaluating multimodal agents on real mobile-device tasks, testing GUI grounding, navigation, and multi-step task completion in mobile environments.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
MobileWorld
Modality
multimodal
Primary category
multimodal
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
mobileworld|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about MobileWorld.

Which model scores highest on MobileWorld?

Qwen3.8 Max is currently ranked first with 77.8%.

What does MobileWorld measure?

MobileWorld is a benchmark for evaluating multimodal agents on real mobile-device tasks, testing GUI grounding, navigation, and multi-step task completion in mobile environments.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

3 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.

Rankings

OverallCodingText ArenaPricing

Modalities

All ModelsImage GenerationImage EditingVideo GenerationImage-to-VideoVideo EditingText-to-SpeechSpeech-to-TextEmbeddings

Benchmarks

All BenchmarksReasoningMathCoding

Vendors

All VendorsOpenAIAnthropicGoogle
llmboard.aiCopyright 2026 llmboard.ai