SCHEDBench (Plain): leaderboard

SCHEDBench (2026) verbalizes canonical job-shop, project-scheduling, nurse-rostering and timetabling instances as natural-language problems and checks whether large language models produce constraint-feasible schedules. Feasibility is the share of instances whose output satisfies all hard constraints under an exact OR-Tools verifier, in percent, higher is better, on the plain rendering with canonical entity names and no reordering.

Metric: Feasibility rate (%; share of SCHEDBench natural-language scheduling instances whose model output satisfies all hard constraints, verified by OR-Tools CP-SAT; six canonical job-shop, project-scheduling, nurse-rostering and timetabling families; greedy decoding, zero-shot, no external solver). Source: arxiv.org. Saturation forecast: Around February 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.5 (2026-04-23)84#33
2Gemini 3 Flash (Preview)52.1#141
3Qwen 3.5 27B39.8#358
4Qwen 3.5 397B A17B38.7#242
5Qwen 3.5 122B A10B28.9#329
6Claude Opus 4.618.3#100
7Claude Sonnet 4.618.1#158
8GPT-5.4 (2026-03-05)11.5#84
9Gemini 3.1 Flash Lite10.2#363
10Llama 3.3 70B10#1511
11GPT-5.4 Mini (2026-03-17)9.8#285
12Claude Haiku 4.59.6#568
13Llama 4 Maverick8.5#1105

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

Interactive version: theaggregate.ai/benchmark?slug=schedbench-plain · How It Works · Data refreshed daily, snapshot 2026-11-12.