Leaderboard
PortBench
Multi-asset portfolio management across six asset classes. It pairs a static QA set with a five-stage decision pipeline whose allocation stage is scored on how well it captures cross-asset correlation, under stress windows and three risk profiles.
PortBench arXiv v6 (2026-10-09)
CEPS (0-1), higher is better. 10 models.
Updated 9 Oct 2026
- GLM-5.10.384
- Qwen3.6-Plus0.300
- Qwen3.7-Max0.292
- Kimi K2.60.274
- Qwen3.6-35B-A3B0.272
- DS-V4-Pro0.266
- DB-2.0-Pro0.263
- HY3-Preview0.258
- DB-2.0-Lite0.244
- DS-V4-Flash0.226
PortBench arXiv v6 (2026-10-09)
CEPS (0-1), higher is better. 10 models.
Updated 9 Oct 2026
- 1GLM-5.10.384
- 2Qwen3.6-Plus0.300
- 3Qwen3.7-Max0.292
- 4Kimi K2.60.274
- 5Qwen3.6-35B-A3B0.272
- 6DS-V4-Pro0.266
- 7DB-2.0-Pro0.263
- 8HY3-Preview0.258
- 9DB-2.0-Lite0.244
- 10DS-V4-Flash0.226
| 1 | GLM-5.1 | Zhipu AI | 0.384 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
|---|---|---|---|---|---|
| 2 | Qwen3.6-Plus | Qwen | 0.300 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
| 3 | Qwen3.7-Max | Qwen | 0.292 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
| 4 | Kimi K2.6 | Moonshot AI | 0.274 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
| 5 | Qwen3.6-35B-A3B | Qwen | 0.272 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
| 6 | DS-V4-Pro | DeepSeek | 0.266 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
| 7 | DB-2.0-Pro | Not stated | 0.263 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
| 8 | HY3-Preview | Tencent | 0.258 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
| 9 | DB-2.0-Lite | Not stated | 0.244 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
| 10 | DS-V4-Flash | DeepSeek | 0.226 | pipeline, balanced risk profile | Paper Table 2 Reported by the authors, 9 Oct 2026 |
PortBench arXiv v6 (2026-10-09)
mean QA score (0-1), higher is better. 10 models.
Updated 9 Oct 2026
- DS-V4-Flash0.819
- Qwen3.7-Max0.819
- DS-V4-Pro0.818
- DB-2.0-Lite0.804
- DB-2.0-Pro0.787
- Qwen3.6-Plus0.783
- GLM-5.10.757
- Qwen3.6-35B-A3B0.684
- HY3-Preview0.624
- Kimi K2.60.511
PortBench arXiv v6 (2026-10-09)
mean QA score (0-1), higher is better. 10 models.
Updated 9 Oct 2026
- 1DS-V4-Flash0.819
- 1Qwen3.7-Max0.819
- 3DS-V4-Pro0.818
- 4DB-2.0-Lite0.804
- 5DB-2.0-Pro0.787
- 6Qwen3.6-Plus0.783
- 7GLM-5.10.757
- 8Qwen3.6-35B-A3B0.684
- 9HY3-Preview0.624
- 10Kimi K2.60.511
| 1 | DS-V4-Flash | DeepSeek | 0.819 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |
|---|---|---|---|---|---|
| 1 | Qwen3.7-Max | Qwen | 0.819 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |
| 3 | DS-V4-Pro | DeepSeek | 0.818 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |
| 4 | DB-2.0-Lite | Not stated | 0.804 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |
| 5 | DB-2.0-Pro | Not stated | 0.787 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |
| 6 | Qwen3.6-Plus | Qwen | 0.783 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |
| 7 | GLM-5.1 | Zhipu AI | 0.757 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |
| 8 | Qwen3.6-35B-A3B | Qwen | 0.684 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |
| 9 | HY3-Preview | Tencent | 0.624 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |
| 10 | Kimi K2.6 | Moonshot AI | 0.511 | static QA, mean over T1-T7 (secondary) | Paper Table 1 Reported by the authors, 9 Oct 2026 |