VEHBench - Policy-Conditioned Selection: leaderboard

VEHBench (2026) is a stage-local diagnostic benchmark for LLM-assisted design of vibration energy harvesters for battery-free IoT, scored against a physics oracle. Kendall tau-b from -1 to 1 between the model ranking of feasible candidates and the oracle ranking under a stated deployment policy; higher is better.

Metric: P4 Kendall tau-b (-1 to 1): rank agreement between the model ranking of a feasible candidate pool and the oracle ranking under an explicit deployment policy; LLM-assisted vibration energy harvester design against a physics oracle; one complete run per model. Source: arxiv.org. Saturation forecast: Estimated already saturated. 12 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.40.89#123
2Qwen 3.6 Plus0.88#222
3DeepSeek V30.86#716
4MiMo-V2.5-Pro (Non-reasoning)0.84#279 (MiMo-V2.5-Pro)
5Claude Sonnet 4.60.84#161
6Hy3-preview (Reasoning)0.84#316 (Hy3-preview)
7Qwen 3 Max0.84#403
8DeepSeek R10.83#473
9Gemini 3.1 Pro (Preview)0.82#94
10DeepSeek V4 Pro (Non-reasoning)0.79#188 (DeepSeek V4 Pro)
11O4 Mini0.78#353
12Llama 3.3 70B0.71#1498

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

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