TimeSage-MT: leaderboard
Time series data inform critical decisions across many real-world domains. While large language model (LLM) agents can analyze data through natural language and tools, it remains unclear whether they can conduct reliable time series analysis across multi-turn conversations. Existing benchmarks focus on single-step tasks such as forecasting and anomaly detection, overlooking practical workflows whe
Metric: Overall (self-reported). Source: benchmarklist.com. Saturation forecast: Around July 2027. 6 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GLM-5.1 | 40.5 | #97 |
| 2 | Claude Sonnet 4.6 | 40.44 | #90 |
| 3 | GPT-5.3 Codex | 39.49 | #69 |
| 4 | Qwen 3.5 122B A10B | 37.34 | #173 |
| 5 | MiniMax-M2.7 | 36.44 | #258 |
| 6 | Gemini 3 Flash (Preview) | 35.21 | #82 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=timesage-mt · How It Works · Data refreshed daily, snapshot 2026-10-20.