TLDR
Agentic AI tools can be broadly grouped into three categories: Android agents, Desktop / OS-level agents, and Web (browser-based) agents.
This article lists 14 leading agentic AI tools, selected directly from widely used benchmarks AndroidWorld, OSWorld, and WebArena and summarizes where each tool fits best.
This overview is based on benchmark visibility and tool focus, not on production readiness or commercial adoption.
Android Agents
Benchmark: Evaluated using AndroidWorld,
AndroidWorld evaluates autonomous agents in fully functional android environment, focusing on cross-app, multi step mobile task such as switching between real-world end to end.
The tasks are executed directly with in a realistic Android OS setting using actual applications, with success verified through system-state based rewards signals rather than text matching.
This makes AndroidWorld a strong benchmark for assessing mobile UI grounding and multi-process task execution.
However, it still remains limited to fixed set of task templates and doesn’t capture long-term stability in real production.
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AGI-0 is first ranked on the Android world leaderboard. It focuses on complex system level of mobile workflows and cross app cooperation, reaching the highest reported success rate on benchmark.
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AskUI is #2 on AndroidWorld. It is vision based enable it to automate any native apps just through visual understanding, without relying on UI structures.
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DroidRun is a mobile-focused agent evaluated on AndroidWorld. It combines visual signals with Android UI structure to execute tasks reliably on real devices.
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Surfer 2 is ranked #6. It is cross platform AI agent developed important for research and benchmarking. It shows how far autonomous agent can go in controlling computer across web, desktop, and mobile environments.
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Gbox.ai is ranked #7. It is a high-security enterprise platform focused on training evaluating grounding AI agents in controlled environments.
Desktop & OS- Level Agents
Benchmark: Evaluated using OSworld
OSWorld is an execution based benchmark that evaluates multimodal AI agents on real desktop operating systems including Windows, macOS and Ubuntu.
It measures task success across hundreds of real-world desktop tasks, including web usage, various native applications, file systems and cross-app workflows, based on actual execution outcomes rather than text matching.
Because agents have to complete tasks end to end on real systems, OSWorld is generally seen as reliable of practical OS-level capability.
At the same time, the huge gap between human performance (over 72.36%) and current AI agents highlights ongoing limitations in GUI grounding and operational understanding.
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Ranked #1 on the OS World verified result leaderboard (score: 66.2, Nov 2025)
AskUIVisionAgent shows powerful generalization across desktop environment using visual understanding to interact with native application without selectors or application-specific integration.
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It ranked #2 on OSWorld(45.2)
A research-focused GUI agent leveraging test-time scaling and RL-based grounding to execute multi-step desktop tasks in dynamic environments.
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OpenAI CUA( Computer-Using- Agent)
Ranked #3 on OSWorld(42.9)
OpenAI’s Computer-Using Agent focuses on real-world desktop task execution, combining large reasoning models with reinforcement-learned UI interaction capabilities.
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Ranked #4 on OSWorld (42.5)
A specialized GUI agent optimized for UI grounding and end-to-end desktop task execution, commonly used as a reference system in academic benchmarks and evaluations.
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Ranked #5 on OSWorld (41.4). It’s a hybrid agent integrating multimodal reasoning and execution control, designed to achieve stable and reproducible OS-level task execution.
Web Agents (Browser-Based Submissions)
Benchmark: Evaluated using WebArena.
WebArena is a standalone, self-hostable web environment designed for building and evaluating autonomous agents.
It creates websites from multiple categories, with functionality and data mimicking real-world systems, including social forums, online shopping platforms, content management systems, collaborative development tools , maps and wikis.
This benchmark measures an agent ablilty to interpret high level natural languange instructions and transltate them into concrete web based interactions. Each task comes with with annotated programmatic validation of functional correctness.
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Ranked #1 on WebArena (71.2%).
A browser-based agent configuration evaluated for web navigation and form-based tasks, representing the strongest reported performance in current WebArena submissions.
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Ranked #2 on WebArena (68.0%).
A benchmark submission combining Claude-based reasoning with additional execution tooling via GBOX’s Model Context Protocol, evaluated under WebArena conditions.
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IBM CUGA (Configurable Generalist Agent)
Ranked #5 on WebArena (61.7%).
An open-source generalist agent framework developed by IBM Research, capable of browser-based task execution and evaluated on WebArena as a configurable agent setup.
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Ranked #6 on WebArena (58.1%).
OpenAI’s Computer-Using Agent evaluated on browser based interaction tasks such as navigation and form completion within the WebArena benchmark.
Conclusion
Benchmarks like AndroidWorld, OSWorld, and WebArena reveal a clear pattern:
- Android agents focus on cross-app coordination on real devices
- Desktop / OS-level agents emphasize visual grounding and generalization across native applications
- Web agents are evaluated as browser-based submissions, optimized for SaaS workflows and web navigation
Rather than a single best agent, today’s landscape consists of specialized agents optimized for different environments.
Understanding where an agent operates mobile, desktop, or browser is more important than comparing raw scores across benchmarks.
As agentic AI matures, benchmarks increasingly reflect capability boundaries, not just leaderboard rankings making them a useful lens for understanding where each tool fits best.