DeepPlanning
We show this table for reference; we do not rank on it.
A long-horizon planning benchmark that tests whether agents can optimize under explicit time, budget, and feasibility constraints.
Benchmark score on DeepPlanning — November 13, 2026
We compile the DeepPlanning rows from provider self-reports and secondary reports. Qwen3.7 Plus leads the table at 62.3%, followed by Qwen3.6 Plus (41.5%) and Qwen3.5 397B (37.6%). We do not use these results to rank models overall.
Qwen3.7 Plus
Alibaba
Reported by AlibabaQwen3.6 Plus
Alibaba
Reported by AlibabaQwen3.5 397B
Alibaba
Reported by Alibaba7 modelsAgenticCurrentDisplay onlyUpdated November 13, 2026
Benchmark score table (7 models)
None of the 7 results on this page has a documented run by the benchmark or an independent evaluator: 4 reported by the labs that built the models and 3 reported in another publisher’s document.
| Rank | Model / configuration | Score | Who ran it | Parameters (B) | Open / closed |
|---|---|---|---|---|---|
| 1 | Qwen3.7 PlusAlibabaReported by Alibaba | 62.3% | Reported by Alibaba | Not reported | Closed |
| 2 | Qwen3.6 PlusAlibabaReported by Alibaba | 41.5% | Reported by Alibaba | Not reported | Closed |
| 3 | Qwen3.5 397BAlibabaReported by Alibaba | 37.6% | Reported by Alibaba | Not reported | Open |
| 4 | Claude Opus 4.5AnthropicAnother lab’s comparison table | 26.4% | Another lab’s comparison table | Not reported | Closed |
| 5 | Qwen3.6-35B-A3BAlibabaReported by Alibaba | 25.9% | Reported by Alibaba | Not reported | Open |
| 6 | GLM-5Z.AIAnother lab’s comparison table | 14.6% | Another lab’s comparison table | Not reported | Open |
| 7 | Kimi K2.5Moonshot AIAnother lab’s comparison table | 14.4% | Another lab’s comparison table | Not reported | Open |
- Lab-reported
- Benchmark-run
- Independent
Among the reported DeepPlanning rows, Qwen3.7 Plus is first at 62.3%. The third row is 24.7 points behind. The broader top-10 range is 47.9 points, so the table still separates the published systems.
7 models have been evaluated on DeepPlanning. The benchmark falls in the Agentic category. DeepPlanning is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About DeepPlanning
Year
2026
Tasks
Travel planning and constrained shopping
Format
Long-horizon planning benchmark
Difficulty
Constrained agent planning
DeepPlanning focuses on global constrained optimization rather than local next-step reasoning. It is useful because many agents can execute short actions but still fail when they must gather information and plan coherently over a long horizon under hard constraints.
Freshness and provenance
Version
DeepPlanning 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
Questions
What does DeepPlanning measure?
A long-horizon planning benchmark that tests whether agents can optimize under explicit time, budget, and feasibility constraints.
Which model scores highest on DeepPlanning?
Qwen3.7 Plus by Alibaba currently leads with a score of 62.3% on DeepPlanning.
How many models are evaluated on DeepPlanning?
7 AI models have published results on DeepPlanning in the BenchLM catalog.
Compare top models on DeepPlanning
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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