MMMU-Pro
A multimodal reasoning benchmark used in frontier model evaluation.
A curated library of public AI agent benchmarks, leaderboards, papers, tools, articles, and reports with editorial judgment.
A multimodal reasoning benchmark used in frontier model evaluation.
A 500-problem math benchmark built from the held-out MATH test split.
A benchmark for coding solutions to realistic scientific research problems.
An evaluation for coding agents that use terminal tools to complete tasks.
A leaderboard for a benchmark focused on next-generation assistants with augmented capabilities such as tooling and search.
A leaderboard for evaluating how well models select, format, and execute tool or function calls.
A benchmark proposal for evaluating LLMs as agents across multiple environments and task categories.
A platform for datasets, evaluators, experiments, tracing, and production quality monitoring for LLM and agent applications.
A public dashboard and dataset for finding benchmark signals and leaderboard snapshots.
A field note on why benchmarks matter when agents move from demos to real work and the cost of judgment becomes part of the workflow.
An engineering article on patterns for building agent systems, from workflows to more autonomous agents.