TimeSage-MT - L2 Multi-Skill Analysis: leaderboard
Metric: Outcome score (%) on the 60 L2 multi-skill analysis tasks (5-12 turns, 2-4 dependent analytical steps): per-task mean of the applicable outcome dimensions (numerical accuracy, factual verification, GPT-5.4-judged analytical quality and code correctness, plus decision making at L4); Code-Enabled Reasoning setting (the model writes Python, a sandbox runs it, the model answers from stdout; 240 multi-turn time-series analysis tasks over 8 domains), temperature 0, reasoning effort high where supported and medium for GPT-5.3-Codex; higher is better. Source: arxiv.org. Saturation forecast: Around 2029. 6 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Claude Sonnet 4.6 | 38.3 |
| 2 | GLM-5.1 | 37.5 |
| 3 | GPT-5.3 Codex | 34.96 |
| 4 | Qwen 3.5 122B A10B | 33.63 |
| 5 | MiniMax-M2.7 | 33.42 |
| 6 | Gemini 3 Flash (Preview) | 31.74 |
Interactive version: theaggregate.ai/benchmark?slug=timesage-mt-l2-multi-skill-analysis · How It Works · Data refreshed daily, snapshot 2026-09-29.