reasoning benchmark
DS-Arena-Code
Data Science Arena Code benchmark for evaluating LLMs on realistic data science code generation tasks. Tests capabilities in complex data processing, analysis, and programming across popular Python libraries used in data science workflows.
Updated Aug 11, 2026
Models1
Model coverage1
MetricScore
EvidenceB
DS-Arena-Code Ranking
Higher score ranks better on this benchmark.
| 01 | DE | 63.1% | 100.0% | 1 | C |
DS-Arena-Code Highlights
The leading models and scores on this benchmark.
What is DS-Arena-Code?
What DS-Arena-Code measures and how its scores work.
Data Science Arena Code benchmark for evaluating LLMs on realistic data science code generation tasks. Tests capabilities in complex data processing, analysis, and programming across popular Python libraries used in data science workflows.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- DS-Arena-Code
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- ds-arena-code|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about DS-Arena-Code.
Which model scores highest on DS-Arena-Code?
DeepSeek-V2.5 is currently ranked first with 63.1%.
What does DS-Arena-Code measure?
Data Science Arena Code benchmark for evaluating LLMs on realistic data science code generation tasks. Tests capabilities in complex data processing, analysis, and programming across popular Python libraries used in data science workflows.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.