Cloud-OpsBench (TrainTicket) - Evidence-Order Consistency: leaderboard

Metric: Evidence-order consistency (%): mean share of milestone groups established in an admissible causal order, on Cloud-OpsBench's TrainTicket fault cases (part of 754 runtime-verified cases over 57 fault types); the model drives the authors' ReAct agent (Pydantic-validated tools, temperature 0, at most 20 steps, extended thinking disabled) over snapshot-replayed Kubernetes diagnostic tools, from a user query describing the observed failure; higher is better. Source: arxiv.org. Saturation forecast: Around 2030. 10 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3.5 Plus (Non-reasoning)58#123 (Qwen 3.5 Plus)
2DeepSeek V4 Flash (Non-reasoning)56#134 (DeepSeek V4 Flash)
3Qwen 3.5 27B (Non-reasoning)55#183 (Qwen 3.5 27B)
4GPT-553#91
5Claude Sonnet 452#194
6Qwen 3 14B (Non-reasoning)52#524 (Qwen 3 14B)
7Gemini 2.5 Pro51#145
8Qwen 3 235B A22B (Non-reasoning)50#304 (Qwen 3 235B A22B)
9Qwen 3 8B (Non-reasoning)45#667 (Qwen 3 8B)
10Gemini 2.5 Flash (Non-reasoning)42#237 (Gemini 2.5 Flash)

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=cloud-opsbench-trainticket-evidence-order-consistency · How It Works · Data refreshed daily, snapshot 2026-10-11.