ORAgentBench - Hard: leaderboard

ORAgentBench (2026) tests LLM agents on 107 human-reviewed operations research tasks solved end to end, from multi-file operational data to a validated decision, with hidden validators for feasibility and objective quality; the agents run in the Claude Code or Codex harness. This board is the pass rate (%) on the 34 hard tasks, where a pass needs a feasible submission with normalized quality of at least 0.4; higher is better.

Metric: Pass rate (%) on the 34 hard tasks: a task passes when the submission is feasible and its normalized quality reaches 0.4; end-to-end operations research tasks packaged with multi-file operational data, configuration and a submission schema; the agent writes and runs solver code in an isolated Harbor environment (45-minute interaction budget, 5-minute solve limit) and hidden validators score schema and hard-constraint feasibility and normalized objective quality; higher is better. Source: arxiv.org. Saturation forecast: Around June 2027. 14 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.4 (High)20.59#123 (GPT-5.4)
2GPT-5.3 Codex (High)20.59#116 (GPT-5.3 Codex)
3Claude Sonnet 4.614.71#161
4Claude Opus 4.614.71#102
5DeepSeek V4 Pro13.73#188
6Kimi K2.611.76#178
7GLM-5.18.82#179
8DeepSeek V4 Flash5.88#258
9Qwen 3.6 Plus5.88#222
10GLM-55.88#260
11GPT-5.4 Mini (High)5.88#389 (GPT-5.4 Mini)
12MiniMax-M2.72.94#518
13Qwen 3.5 Plus2.94#232
14MiMo-V2.5-Pro2.94#279

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=oragentbench-hard · How It Works · Data refreshed daily, snapshot 2026-11-13.