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multimodal benchmark

AITZ_EM Leaderboard

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 17, 2026

Models3
Model coverage3
MetricScore
EvidenceB

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AITZ_EM Ranking

Higher score ranks better on this benchmark.

3 rows
Columns

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Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelACQwen2.5 VL 72B InstructAlibaba Cloud / Qwen TeamScore83.2%Percentile100.0%Participants3EvidenceCEvaluatedAug 17, 2026
Rank02ModelACQwen2.5 VL 32B InstructAlibaba Cloud / Qwen TeamScore83.1%Percentile50.0%Participants3EvidenceCEvaluatedAug 17, 2026
Rank03ModelACQwen2.5 VL 7B InstructAlibaba Cloud / Qwen TeamScore81.9%Percentile0.0%Participants3EvidenceCEvaluatedAug 17, 2026

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%

AITZ_EM Score Distribution

A closer view of the leading scores on this benchmark.

AITZ_EM

The Top AI Models for AITZ_EM

The first five results on this benchmark, with official price and output speed added where the model identity can be matched.

Ranking basisThis aitz_em 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.

  1. 01
    AC
    Qwen2.5 VL 72B InstructAlibaba Cloud / Qwen Team
    Score
    83.2%

    Strengths

    • Ranks #1 of 3 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures AITZ_EM, not total model capability
  2. 02
    AC
    Qwen2.5 VL 32B InstructAlibaba Cloud / Qwen Team
    Score
    83.1%

    Strengths

    • Ranks #2 of 3 compared models
    • 50th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures AITZ_EM, not total model capability
  3. 03
    AC
    Qwen2.5 VL 7B InstructAlibaba Cloud / Qwen Team
    Score
    81.9%
    Price
    $0.35 input / $1.1 output per 1M tokens

    Strengths

    • Ranks #3 of 3 compared models
    • 0th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures AITZ_EM, not total model capability

Selection summary

Best AI Models for AITZ_EM

Qwen2.5 VL 72B Instruct currently leads AITZ_EM with 83.2%. 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.

Benchmark rank #1Qwen2.5 VL 72B Instruct83.2%Benchmark rank #2Qwen2.5 VL 32B Instruct83.1%Benchmark rank #3Qwen2.5 VL 7B Instruct81.9% · $0.35 input / $1.1 output per 1M tokens

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.