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multimodal benchmark

AITZ_EM

Android-In-The-Zoo (AitZ) benchmark for evaluating autonomous GUI agents on smartphones. Contains 18,643 screen-action pairs with chain-of-action-thought annotations spanning over 70 Android apps. Designed to connect perception (screen layouts and UI elements) with cognition (action decision-making) for natural language-triggered smartphone task completion.

Updated Aug 11, 2026

Models3
Model coverage3
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

AITZ_EM Ranking

Higher score ranks better on this benchmark.

3 rows
Columns

Show columns

01ACQwen2.5 VL 72B InstructAlibaba Cloud / Qwen Team83.2%100.0%3CAug 11, 2026
02ACQwen2.5 VL 32B InstructAlibaba Cloud / Qwen Team83.1%50.0%3CAug 11, 2026
03ACQwen2.5 VL 7B InstructAlibaba Cloud / Qwen Team81.9%0.0%3CAug 11, 2026

AITZ_EM Score Distribution

A closer view of the leading scores on this benchmark.

AITZ_EM

AITZ_EM Highlights

The leading models and scores on this benchmark.

Rank #1Qwen2.5 VL 72B Instruct83.2%Rank #2Qwen2.5 VL 32B Instruct83.1%Rank #3Qwen2.5 VL 7B Instruct81.9%

What is AITZ_EM?

What AITZ_EM measures and how its scores work.

Android-In-The-Zoo (AitZ) benchmark for evaluating autonomous GUI agents on smartphones. Contains 18,643 screen-action pairs with chain-of-action-thought annotations spanning over 70 Android apps. Designed to connect perception (screen layouts and UI elements) with cognition (action decision-making) for natural language-triggered smartphone task completion.

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

Family
AITZ_EM
Modality
multimodal
Primary category
multimodal
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
aitz-em|llm-stats-current

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

FAQ

Common questions about AITZ_EM.

Which model scores highest on AITZ_EM?

Qwen2.5 VL 72B Instruct is currently ranked first with 83.2%.

What does AITZ_EM measure?

Android-In-The-Zoo (AitZ) benchmark for evaluating autonomous GUI agents on smartphones. Contains 18,643 screen-action pairs with chain-of-action-thought annotations spanning over 70 Android apps. Designed to connect perception (screen layouts and UI elements) with cognition (action decision-making) for natural language-triggered smartphone task completion.

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.