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.
Gemini 2.0 Flash from Google currently leads the Natural2Code leaderboard with a score of 0.929 across 8 evaluated AI models.
Gemini 2.0 Flash leads with 92.9%, followed by Gemini 1.5 Pro at 85.4% and Gemma 3 27B at 84.5%.
Progress Over Time
Interactive timeline showing model performance evolution on Natural2Code
Natural2Code Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Google | — | — | — | ||
| 2 | Google | — | — | — | ||
| 3 | Google | 27B | — | — | ||
| 4 | Google | 12B | — | — | ||
| 5 | Google | — | — | — | ||
| 6 | Google | 8B | — | — | ||
| 7 | Google | 4B | — | — | ||
| 8 | Google | 1B | — | — |
FAQ
Common questions about Natural2Code.
More evaluations to explore
Related benchmarks in the same category
A challenging dataset of 448 multiple-choice questions written by domain experts in biology, physics, and chemistry. Questions are Google-proof and extremely difficult, with PhD experts reaching 65% accuracy.
A more robust and challenging multi-task language understanding benchmark that extends MMLU by expanding multiple-choice options from 4 to 10, eliminating trivial questions, and focusing on reasoning-intensive tasks. Features over 12,000 curated questions across 14 domains and causes a 16-33% accuracy drop compared to original MMLU.
All 30 problems from the 2025 American Invitational Mathematics Examination (AIME I and AIME II), testing olympiad-level mathematical reasoning with integer answers from 000-999. Used as an AI benchmark to evaluate large language models' ability to solve complex mathematical problems requiring multi-step logical deductions and structured symbolic reasoning.
Massive Multitask Language Understanding benchmark testing knowledge across 57 diverse subjects including STEM, humanities, social sciences, and professional domains
A verified subset of 500 software engineering problems from real GitHub issues, validated by human annotators for evaluating language models' ability to resolve real-world coding issues by generating patches for Python codebases.
Humanity's Last Exam (HLE) is a multi-modal academic benchmark with 2,500 questions across mathematics, humanities, and natural sciences, designed to test LLM capabilities at the frontier of human knowledge with unambiguous, verifiable solutions