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reasoning benchmark

LiveCodeBench v6 Leaderboard

LiveCodeBench v6 is a benchmark for evaluating large language models on code using newly collected programming contest problems.

Updated Sep 5, 2026

Models62
Model coverage62
MetricScore
EvidenceB

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LiveCodeBench v6 Ranking

Higher score ranks better on this benchmark.

30 of 62 rows
Columns

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Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelACQwen3.8-Flash-NextAlibaba Cloud / Qwen TeamScore91.90%Percentile100.00%Participants62EvidenceCEvaluatedSep 8, 2026
Rank02ModelACQwen3.8 FlashAlibaba Cloud / Qwen TeamScore91.90%Percentile98.36%Participants62EvidenceCEvaluatedSep 8, 2026
Rank03ModelACQwen3.7 MaxAlibaba Cloud / Qwen TeamScore91.60%Percentile96.72%Participants62EvidenceCEvaluatedSep 8, 2026
Rank04ModelSASakana NamazuSakana AIScore90.33%Percentile95.08%Participants62EvidenceCEvaluatedSep 8, 2026
Rank05ModelACQwen3.8-27BAlibaba Cloud / Qwen TeamScore90.30%Percentile93.44%Participants62EvidenceCEvaluatedSep 8, 2026
Rank06ModelMAKimi K2.6Moonshot AIScore89.60%Percentile91.80%Participants62EvidenceCEvaluatedSep 8, 2026
Rank07ModelACQwen3.7-PlusAlibaba Cloud / Qwen TeamScore89.60%Percentile90.16%Participants62EvidenceCEvaluatedSep 8, 2026
Rank08ModelNVNemotron 3 Ultra (550B A55B)NVIDIAScore89.00%Percentile88.52%Participants62EvidenceCEvaluatedSep 8, 2026
Rank09ModelBYSeed 2.0 ProByteDanceScore87.80%Percentile86.89%Participants62EvidenceCEvaluatedSep 8, 2026
Rank10ModelMIMAI-Thinking-1MicrosoftScore87.70%Percentile85.25%Participants62EvidenceCEvaluatedSep 8, 2026
Rank11ModelACQwen3.6 PlusAlibaba Cloud / Qwen TeamScore87.10%Percentile83.61%Participants62EvidenceCEvaluatedSep 8, 2026
Rank12ModelSTStep-3.5-FlashStepFunScore86.40%Percentile81.97%Participants62EvidenceCEvaluatedSep 8, 2026
Rank13ModelMAKimi K2.5Moonshot AIScore85.00%Percentile80.33%Participants62EvidenceCEvaluatedSep 8, 2026
Rank14ModelZAGLM-4.7Zhipu AIScore84.90%Percentile78.69%Participants62EvidenceCEvaluatedSep 8, 2026
Rank15ModelACQwen3.6-27BAlibaba Cloud / Qwen TeamScore83.90%Percentile77.05%Participants62EvidenceCEvaluatedSep 8, 2026
Rank16ModelACQwen3.5-397B-A17BAlibaba Cloud / Qwen TeamScore83.60%Percentile75.41%Participants62EvidenceCEvaluatedSep 8, 2026
Rank17ModelMAKimi K2-Thinking-0905Moonshot AIScore83.10%Percentile73.77%Participants62EvidenceCEvaluatedSep 8, 2026
Rank18ModelZAGLM-4.6Zhipu AIScore82.80%Percentile72.13%Participants62EvidenceCEvaluatedSep 8, 2026
Rank19ModelOPGPT OSS 120B HighOpenAIScore81.90%Percentile70.49%Participants62EvidenceCEvaluatedSep 8, 2026
Rank20ModelBYSeed 2.0 LiteByteDanceScore81.70%Percentile68.85%Participants62EvidenceCEvaluatedSep 8, 2026
Rank21ModelLAEXAONE 4.5 33BLG AI ResearchScore81.40%Percentile67.21%Participants62EvidenceCEvaluatedSep 8, 2026
Rank22ModelLAK-EXAONE-236B-A23BLG AI ResearchScore80.70%Percentile65.57%Participants62EvidenceCEvaluatedSep 8, 2026
Rank23ModelACQwen3.5-27BAlibaba Cloud / Qwen TeamScore80.70%Percentile63.93%Participants62EvidenceCEvaluatedSep 8, 2026
Rank24ModelXIMiMo-V2-FlashXiaomiScore80.60%Percentile62.30%Participants62EvidenceCEvaluatedSep 8, 2026
Rank25ModelACQwen3.6-35B-A3BAlibaba Cloud / Qwen TeamScore80.40%Percentile60.66%Participants62EvidenceCEvaluatedSep 8, 2026
Rank26ModelGOGemma 4 31BGoogleScore80.00%Percentile59.02%Participants62EvidenceCEvaluatedSep 8, 2026
Rank27ModelACQwen3.5-122B-A10BAlibaba Cloud / Qwen TeamScore78.90%Percentile57.38%Participants62EvidenceCEvaluatedSep 8, 2026
Rank28ModelGOGemma 4 26B-A4BGoogleScore77.10%Percentile55.74%Participants62EvidenceCEvaluatedSep 8, 2026
Rank29ModelIBIBM Granite 4.2 30BIBMScore75.77%Percentile54.10%Participants62EvidenceCEvaluatedSep 8, 2026
Rank30ModelACQwen3.5-35B-A3BAlibaba Cloud / Qwen TeamScore74.60%Percentile52.46%Participants62EvidenceCEvaluatedSep 8, 2026

LiveCodeBench v6 Highlights

The leading models and scores on this benchmark.

LiveCodeBench v6 Score Distribution

A closer view of the leading scores on this benchmark.

LiveCodeBench v6

The Top AI Models for LiveCodeBench v6

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

What is LiveCodeBench v6?

What LiveCodeBench v6 measures and how its scores work.

LiveCodeBench v6 is a benchmark for large language models for code that collects problems from LeetCode, AtCoder, and CodeForces and annotates them with release dates.

It measures code generation, self-repair, code execution, and test output prediction, reported as a Score ratio.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
LiveCodeBench v6
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 LiveCodeBench v6.

Which model scores highest on LiveCodeBench v6?

Qwen3.8-Flash-Next is currently ranked first with 91.90%.

What are the top three models on LiveCodeBench v6?

The current leaders are Qwen3.8-Flash-Next (91.90%), Qwen3.8 Flash (91.90%), and Qwen3.7 Max (91.60%).

Which LiveCodeBench v6 model has the lowest official input price?

Step-3.5-Flash has the lowest matched official input price at $0.10 input / $0.30 output per 1M tokens.

Which models are fastest among LiveCodeBench v6 results?

The fastest matched records are GPT OSS 120B High (100.00 tok/s via OpenAI), GLM-4.6 (85.00 tok/s via DeepInfra), and K-EXAONE-236B-A23B (50.00 tok/s via FriendliAI).

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 LiveCodeBench v6 measure?

It measures code generation, self-repair, code execution, and test output prediction, reported as a Score ratio.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

62 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 #1Qwen3.8-Flash-Next91.90%
Rank #2Qwen3.8 Flash91.90%
Rank #3Qwen3.7 Max91.60%
Rank #4Sakana Namazu90.33%

Ranking basisThis livecodebench v6 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
    AC
    Qwen3.8-Flash-NextAlibaba Cloud / Qwen Team
    Score
    91.90%

    Strengths

    • Ranks #1 of 62 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures LiveCodeBench v6, not total model capability
  2. 02
    AC
    Qwen3.8 FlashAlibaba Cloud / Qwen Team
    Score
    91.90%
    Price
    $0.15 input / $0.47 output per 1M tokens

    Strengths

    • Ranks #2 of 62 compared models
    • 98th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures LiveCodeBench v6, not total model capability
  3. 03
    AC
    Alibaba Cloud / Qwen Team
    Score
    91.60%
    Price
    $2.5 input / $7.5 output per 1M tokens

    Strengths

    • Ranks #3 of 62 compared models
    • 97th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures LiveCodeBench v6, not total model capability
  4. 04
    SA
    Sakana AI
    Score
    90.33%
    Price
    $0.95 input / $4.0 output per 1M tokens

    Strengths

    • Ranks #4 of 62 compared models
    • 95th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures LiveCodeBench v6, not total model capability
  5. 05
    AC
    Alibaba Cloud / Qwen Team
    Score
    90.30%

    Strengths

    • Ranks #5 of 62 compared models
    • 93th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures LiveCodeBench v6, not total model capability

Selection summary

Best AI Models for LiveCodeBench v6

Qwen3.8-Flash-Next currently leads LiveCodeBench v6 with 91.90%. 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.

Qwen3.7 Max
Sakana Namazu
Qwen3.8-27B
Benchmark rank #1Qwen3.8-Flash-Next91.90%
Benchmark rank #2Qwen3.8 Flash91.90% · $0.15 input / $0.47 output per 1M tokens
Benchmark rank #3Qwen3.7 Max91.60% · $2.5 input / $7.5 output per 1M tokens