JOR-Bench - MAMO Complex LP: leaderboard

JOR-Bench (2026) translates the MAMO Complex LP linear programming problems into Japanese with LLM translation and human post-editing. Models write an optimization program that is executed with OR-Tools available, and a problem counts as solved when the printed value matches the reference; accuracy in percent, higher is better.

Metric: Accuracy (%; MAMO Complex LP linear programming problems, Japanese translation with human post-editing; the model writes a standalone Python program in a fenced block, run with OR-Tools available (300-second and 32 GB limits), correct when the printed value matches the reference within 1e-6; higher is better). Source: arxiv.org. Saturation forecast: Around February 2027. 7 models tracked.

Top models

#ModelScoreOverall rank
1GPT-OSS-120B73.5#700
2Qwen 3 32B50#960
3Qwen3-Swallow-32B-RL-v0.237.5#900
4Qwen 3 8B34.5#1830
5Qwen3-Swallow-8B-RL-v0.210.5#1517
6NVIDIA-Nemotron-Nano-9B-v2-Japanese1#1486

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

Interactive version: theaggregate.ai/benchmark?slug=jor-bench-mamo-complex-lp · How It Works · Data refreshed daily, snapshot 2026-11-13.