DiagFlowBench: leaderboard

Language models increasingly serve as advisory systems in maintenance operations. To prevent hallucination, recent systems ground these models in procedural documentation to constrain them to approved steps. In practice, however, operator queries frequently stray from this path, requiring models to recognise out-of-scope inputs mid-conversation, a dynamic that current benchmarks rarely prioritise.

Metric: Step Accuracy (self-reported). Source: benchmarklist.com. 10 models tracked.

Top models

#ModelScoreOverall rank
1Llama 3.3 70B85#579
2Gemini 2.5 Flash84#245
3Llama 4 Maverick82.8#464
4Llama 4 Scout79.2#656
5GPT-OSS-120B76.2#341
6GPT-4o Mini75.4#599
7Qwen 3 235B A22B73.7#313
8Nemotron 3 Super70.3#335
9Qwen 3 30B A3B70.1#493

Interactive version: theaggregate.ai/benchmark?slug=diagflowbench · How It Works · Data refreshed daily, snapshot 2026-10-20.