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reasoning benchmark

Natural2Code Leaderboard

Natural2Code is a code benchmark comprising 402 problems in Python and Java across 6 domains, selected from natural user queries from online coding services.

Updated Sep 5, 2026

Models8
Model coverage8
MetricScore
EvidenceB

On this page

  • Ranking
  • Highlights
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  • About
  • FAQ

Natural2Code Ranking

Higher score ranks better on this benchmark.

8 rows
Columns

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Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelGOGemini 2.0 FlashGoogleScore92.90%Percentile100.00%Participants8EvidenceCEvaluatedSep 8, 2026
Rank02ModelGOGemini 1.5 ProGoogleScore85.40%Percentile85.71%Participants8EvidenceCEvaluatedSep 8, 2026
Rank03ModelGOGemma 3 27BGoogleScore84.50%Percentile71.43%Participants8EvidenceCEvaluatedSep 8, 2026
Rank04ModelGOGemma 3 12BGoogleScore80.70%Percentile57.14%Participants8EvidenceCEvaluatedSep 8, 2026
Rank05ModelGOGemini 1.5 FlashGoogleScore79.80%Percentile42.86%Participants8EvidenceCEvaluatedSep 8, 2026
Rank06ModelGOGemini 1.5 Flash 8BGoogleScore75.50%Percentile28.57%Participants8EvidenceCEvaluatedSep 8, 2026
Rank07ModelGOGemma 3 4BGoogleScore70.30%Percentile14.29%Participants8EvidenceCEvaluatedSep 8, 2026
Rank08ModelGOGemma 3 1BGoogleScore56.00%Percentile0.00%Participants8EvidenceCEvaluatedSep 8, 2026

Natural2Code Highlights

The leading models and scores on this benchmark.

Natural2Code Score Distribution

A closer view of the leading scores on this benchmark.

Natural2Code

The Top AI Models for Natural2Code

The first five results on this benchmark, with official price and output speed added where the model identity can be matched.

What is Natural2Code?

What Natural2Code measures and how its scores work.

NaturalCodeBench (NCB) is a code benchmark comprising 402 problems in Python and Java across 6 domains.

It reports a Score expressed as a ratio.

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
No
Evaluation key
overall

LLM Stats. 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 92.90%.

What are the top three models on Natural2Code?

The current leaders are Gemini 2.0 Flash (92.90%), Gemini 1.5 Pro (85.40%), and Gemma 3 27B (84.50%).

Which Natural2Code model has the lowest official input price?

No matched official input price is currently available.

Which models are fastest among Natural2Code results?

The fastest matched records are Gemini 2.0 Flash (183.00 tok/s via Google), Gemini 1.5 Flash (150.00 tok/s via Google), and Gemini 1.5 Flash 8B (150.00 tok/s via Google).

Does the highest score result prove overall model quality?

No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.

What does Natural2Code measure?

It reports a Score expressed as a ratio.

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?

No. This benchmark is shown for reference but does not contribute to the overall score.

Rank #1Gemini 2.0 Flash92.90%
Rank #2Gemini 1.5 Pro85.40%
Rank #3Gemma 3 27B84.50%
Rank #4Gemma 3 12B80.70%

Ranking basisThis natural2code AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.

  1. 01
    GO
    Gemini 2.0 FlashGoogle
    Score
    92.90%
    Speed
    Up to 183.00 tok/s via Google

    Strengths

    • Ranks #1 of 8 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Natural2Code, not total model capability
  2. 02
    GO
    Gemini 1.5 ProGoogle
    Score
    85.40%
    Speed
    Up to 85.00 tok/s via Google

    Strengths

    • Ranks #2 of 8 compared models
    • 86th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Natural2Code, not total model capability
  3. 03
    GO
    Google
    Score
    84.50%
    Speed
    Up to 33.00 tok/s via DeepInfra

    Strengths

    • Ranks #3 of 8 compared models
    • 71th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Natural2Code, not total model capability
  4. 04
    GO
    Google
    Score
    80.70%
    Speed
    Up to 33.00 tok/s via DeepInfra

    Strengths

    • Ranks #4 of 8 compared models
    • 57th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Natural2Code, not total model capability
  5. 05
    GO
    Google
    Score
    79.80%
    Speed
    Up to 150.00 tok/s via Google

    Strengths

    • Ranks #5 of 8 compared models
    • 43th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Natural2Code, not total model capability

Selection summary

Best AI Models for Natural2Code

Gemini 2.0 Flash currently leads Natural2Code with 92.90%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.

Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.

Gemma 3 27B
Gemma 3 12B
Gemini 1.5 Flash
Benchmark rank #1Gemini 2.0 Flash92.90% · Up to 183.00 tok/s via Google
Benchmark rank #2Gemini 1.5 Pro85.40% · Up to 85.00 tok/s via Google
Benchmark rank #3Gemma 3 27B84.50% · Up to 33.00 tok/s via DeepInfra