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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

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

Natural2Code Ranking

Higher score ranks better on this benchmark.

8 rows
Columns

Show columns

01GOGemini 2.0 FlashGoogle92.9%100.0%8CAug 11, 2026
02GOGemini 1.5 ProGoogle85.4%85.7%8CAug 11, 2026
03GOGemma 3 27BGoogle84.5%71.4%8CAug 11, 2026
04GOGemma 3 12BGoogle80.7%57.1%8CAug 11, 2026
05GOGemini 1.5 FlashGoogle79.8%42.9%8CAug 11, 2026
06GOGemini 1.5 Flash 8BGoogle75.5%28.6%8CAug 11, 2026
07GOGemma 3 4BGoogle70.3%14.3%8CAug 11, 2026
08GOGemma 3 1BGoogle56.0%0.0%8CAug 11, 2026

Natural2Code Score Distribution

A closer view of the leading scores on this benchmark.

Natural2Code

Natural2Code Highlights

The leading models and scores on this benchmark.

Rank #1Gemini 2.0 Flash92.9%Rank #2Gemini 1.5 Pro85.4%Rank #3Gemma 3 27B84.5%Rank #4Gemma 3 12B80.7%

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.