reasoning benchmark
Natural2Code
NaturalCodeBench (NCB) is a challenging code benchmark designed to mirror the complexity and variety of real-world coding tasks. It comprises 402 high-quality problems in Python and Java, selected from natural user queries from online coding services, covering 6 different domains.
Updated Aug 11, 2026
Models8
Model coverage8
MetricScore
EvidenceB
Natural2Code Ranking
Higher score ranks better on this benchmark.
| 1 | GO | 92.9% | 100.0% | 8 | C | |
| 2 | GO | 85.4% | 85.7% | 8 | C | |
| 3 | GO | 84.5% | 71.4% | 8 | C | |
| 4 | GO | 80.7% | 57.1% | 8 | C | |
| 5 | GO | 79.8% | 42.9% | 8 | C | |
| 6 | GO | 75.5% | 28.6% | 8 | C | |
| 7 | GO | 70.3% | 14.3% | 8 | C | |
| 8 | GO | 56.0% | 0.0% | 8 | C |
Natural2Code Score Distribution
A closer view of the leading scores on this benchmark.
Natural2Code Highlights
The leading models and scores on this benchmark.
What is Natural2Code?
What Natural2Code measures and how its scores work.
NaturalCodeBench (NCB) is a challenging code benchmark designed to mirror the complexity and variety of real-world coding tasks. It comprises 402 high-quality problems in Python and Java, selected from natural user queries from online coding services, covering 6 different domains.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Natural2Code
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- natural2code|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Natural2Code.
Which model scores highest on Natural2Code?
Gemini 2.0 Flash is currently ranked first with 92.9%.
What does Natural2Code measure?
NaturalCodeBench (NCB) is a challenging code benchmark designed to mirror the complexity and variety of real-world coding tasks. It comprises 402 high-quality problems in Python and Java, selected from natural user queries from online coding services, covering 6 different domains.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
8 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.