AgentsOnline
AgentBench
Measures language-model agents across operating systems, databases, games, web shopping, and other interactive environments.
- Task count
- 8
There are 31 agents in the index.
31 benchmarks
AgentsOnline
Measures language-model agents across operating systems, databases, games, web shopping, and other interactive environments.
AgentsOnline
Evaluates embodied agents in interactive simulated indoor scenes with object manipulation and navigation.
AgentsOnline
Measures agents that learn high-level policies in text environments and execute the same household goals in embodied worlds.
AgentsOnline
Measures autonomous agents on dynamically generated tasks across real Android applications.
AgentsOnline
Tests grounded language understanding by asking an agent to navigate a grid world to a described object.
AgentsOnline
Evaluates strategic planning, negotiation, and natural-language coordination by agents playing the board game Diplomacy.
AgentsOnline
Measures reinforcement-learning agents across a survival game designed to expose a broad spectrum of capabilities.
AgentsOnline
Evaluates reinforcement-learning agents on survival, exploration, resource collection, and technology-tree achievements.
AgentsOnline
Measures agents on professional customer-relationship-management tasks in realistic business scenarios.
AgentsOnline
Tests agents that navigate a simulated home to gather visual evidence and answer a question.
AgentsOnline
Evaluates agents on multistep financial work involving web research, files, multimodal inputs, code, and calculations.
AgentsOnline
Measures agents in human-authored interactive-fiction games through a common learning interface.
AgentsOnline
Tests lifelong robot learning under spatial-relation distribution shifts in simulated manipulation tasks.
AgentsOnline
Measures open-ended embodied agents across thousands of Minecraft tasks with an internet-scale knowledge base.
AgentsOnline
Measures mobile agents on instructions that require perception, planning, and actions in Android applications.
AgentsOnline
Measures multimodal agents on reproducible, open-ended tasks in real desktop applications; the verified release repairs the original task set.
AgentsOnline
Measures a language-model agent on tactical decision making in competitive Pokémon battles.
AgentsOnline
Evaluates robot policies on everyday kitchen manipulation tasks in a large-scale simulation framework.
AgentsOnline
Measures agent reasoning, planning, spatial understanding, learning, and handling of randomness across six games.
AgentsOnline
Tests agents on realistic enterprise text-to-SQL workflows with long contexts and cloud or local databases.
AgentsOnline
Evaluates generation and execution of household activity programs in simulated 3D homes.
AgentsOnline
Tests exploration, goal discovery, world-model building, and planning in novel interactive environments.
AgentsOnline
Measures grounded language understanding by training agents to follow generated instructions in grid worlds.
AgentsOnline
Measures general assistants on real-world questions requiring reasoning, tools, browsing, and multimodal inputs.
Published by AI Benchmark Index. How we check each benchmark.