multimodal benchmark
AndroidWorld Success Rate (SR) benchmark - A dynamic benchmarking environment for autonomous agents operating on Android devices. Evaluates agents on 116 programmatic tasks across 20 real-world Android apps using multimodal inputs (screen screenshots, accessibility trees, and natural language instructions). Measures success rate of agents completing tasks like sending messages, creating calendar events, and navigating mobile interfaces. Published at ICLR 2025. Best current performance: 30.6% success rate (M3A agent) vs 80.0% human performance.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | AC | 71.1% | 100.0% | 8 | C | |
| 02 | AC | 66.4% | 85.7% | 8 | C | |
| 03 | AC | 64.2% | 71.4% | 8 | C | |
| 04 | AC | 63.7% | 57.1% | 8 | C | |
| 05 | AC | 63.7% | 42.9% | 8 | C | |
| 06 | AC | 35.0% | 28.6% | 8 | C | |
| 07 | AC | 25.5% | 14.3% | 8 | C | |
| 08 | AC | 22.0% | 0.0% | 8 | C |
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
What AndroidWorld_SR measures and how its scores work.
AndroidWorld Success Rate (SR) benchmark - A dynamic benchmarking environment for autonomous agents operating on Android devices. Evaluates agents on 116 programmatic tasks across 20 real-world Android apps using multimodal inputs (screen screenshots, accessibility trees, and natural language instructions). Measures success rate of agents completing tasks like sending messages, creating calendar events, and navigating mobile interfaces. Published at ICLR 2025. Best current performance: 30.6% success rate (M3A agent) vs 80.0% human performance.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about AndroidWorld_SR.
Qwen3.5-35B-A3B is currently ranked first with 71.1%.
AndroidWorld Success Rate (SR) benchmark - A dynamic benchmarking environment for autonomous agents operating on Android devices. Evaluates agents on 116 programmatic tasks across 20 real-world Android apps using multimodal inputs (screen screenshots, accessibility trees, and natural language instructions). Measures success rate of agents completing tasks like sending messages, creating calendar events, and navigating mobile interfaces. Published at ICLR 2025. Best current performance: 30.6% success rate (M3A agent) vs 80.0% human performance.
Yes. Higher values rank better for this benchmark.
8 model results are currently shown.
Yes. This benchmark can contribute to the current LLMBoard capability score.