LPS-Bench - Rigid Over-compliance: leaderboard

Metric: Success-conditioned safe rate (%): the share of agent trajectories that meet the case's own safety criterion at every planning and tool-calling step (a benign case is safe when completed with the needed safeguards or paused for clarification, an adversarial case when the agent refuses or halts before harm), among trajectories labeled safe or unsafe by a DeepSeek-R1 evaluator (execution failures excluded); on the 62 benign user-induced cases of risk type OC (literal instructions whose implicit intent calls for a safeguard); LPS-Bench's 570 human-reviewed long-horizon tool-use cases with simulated MCP-style toolkits, each model in one LangChain agent at temperature 1 with up to 100 steps; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1Claude Sonnet 4.570.97#138
2DeepSeek V3.269.35#198
3Claude Sonnet 462.9#194
4Gemini 3 Pro54.84#77
5GPT-550#91
6Gemini 2.5 Pro46.77#145
7Claude 3.5 Sonnet40.32#337
8DeepSeek V3.137.1#260
9GPT-5.127.42#131
10Qwen 3 8B9.68#667
11Qwen 3 32B9.68#424
12Llama 3.1 70B Instruct8.06#548
13Llama 3.1 8B Instruct6.45#1018

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

Interactive version: theaggregate.ai/benchmark?slug=lps-bench-rigid-over-compliance · How It Works · Data refreshed daily, snapshot 2026-10-11.