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general benchmark

NOVA-63 Leaderboard

NOVA-63 is a multilingual evaluation benchmark covering 63 languages and assessing LLM performance across diverse linguistic contexts and tasks.

Updated Sep 5, 2026

Models11
Model coverage11
MetricScore
EvidenceB

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NOVA-63 Ranking

Higher score ranks better on this benchmark.

11 rows
Columns

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Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelACQwen3.5-397B-A17BAlibaba Cloud / Qwen TeamScore59.10%Percentile100.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank02ModelACQwen3.7 MaxAlibaba Cloud / Qwen TeamScore59.00%Percentile90.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank03ModelACQwen3.7-PlusAlibaba Cloud / Qwen TeamScore58.80%Percentile80.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank04ModelACQwen3.5-122B-A10BAlibaba Cloud / Qwen TeamScore58.60%Percentile70.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank05ModelACQwen3.5-27BAlibaba Cloud / Qwen TeamScore58.10%Percentile60.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank06ModelACQwen3.6 PlusAlibaba Cloud / Qwen TeamScore57.90%Percentile50.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank07ModelACQwen3.5-35B-A3BAlibaba Cloud / Qwen TeamScore57.10%Percentile40.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank08ModelACQwen3.5-9BAlibaba Cloud / Qwen TeamScore55.90%Percentile30.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank09ModelACQwen3.5-4BAlibaba Cloud / Qwen TeamScore54.30%Percentile20.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank10ModelACQwen3.5-2BAlibaba Cloud / Qwen TeamScore46.40%Percentile10.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank11ModelACQwen3.5-0.8BAlibaba Cloud / Qwen TeamScore42.40%Percentile0.00%Participants11EvidenceCEvaluatedSep 8, 2026

NOVA-63 Highlights

The leading models and scores on this benchmark.

NOVA-63 Score Distribution

A closer view of the leading scores on this benchmark.

NOVA-63

The Top AI Models for NOVA-63

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

What is NOVA-63?

What NOVA-63 measures and how its scores work.

NOVA-63 is a general multilingual evaluation benchmark covering 63 languages.

NOVA-63 measures LLM performance across diverse linguistic contexts and tasks using the Score metric, reported as a ratio.

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

Family
NOVA-63
Modality
text
Primary category
general
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 NOVA-63.

Which model scores highest on NOVA-63?

Qwen3.5-397B-A17B is currently ranked first with 59.10%.

What are the top three models on NOVA-63?

The current leaders are Qwen3.5-397B-A17B (59.10%), Qwen3.7 Max (59.00%), and Qwen3.7-Plus (58.80%).

Which NOVA-63 model has the lowest official input price?

Qwen3.5-35B-A3B has the lowest matched official input price at $0.25 input / $2.0 output per 1M tokens.

Which models are fastest among NOVA-63 results?

No matched runtime record is currently available.

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 NOVA-63 measure?

NOVA-63 measures LLM performance across diverse linguistic contexts and tasks using the Score metric, reported as a ratio.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

11 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 #1Qwen3.5-397B-A17B59.10%
Rank #2Qwen3.7 Max59.00%
Rank #3Qwen3.7-Plus58.80%
Rank #4Qwen3.5-122B-A10B58.60%

Ranking basisThis nova-63 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
    Qwen3.5-397B-A17BAlibaba Cloud / Qwen Team
    Score
    59.10%
    Price
    $0.60 input / $3.6 output per 1M tokens

    Strengths

    • Ranks #1 of 11 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures NOVA-63, not total model capability
  2. 02
    AC
    Qwen3.7 MaxAlibaba Cloud / Qwen Team
    Score
    59.00%
    Price
    $2.5 input / $7.5 output per 1M tokens

    Strengths

    • Ranks #2 of 11 compared models
    • 90th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures NOVA-63, not total model capability
  3. 03
    AC
    Alibaba Cloud / Qwen Team
    Score
    58.80%
    Price
    $0.50 input / $3.0 output per 1M tokens

    Strengths

    • Ranks #3 of 11 compared models
    • 80th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures NOVA-63, not total model capability
  4. 04
    AC
    Alibaba Cloud / Qwen Team
    Score
    58.60%
    Price
    $0.40 input / $3.2 output per 1M tokens

    Strengths

    • Ranks #4 of 11 compared models
    • 70th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures NOVA-63, not total model capability
  5. 05
    AC
    Alibaba Cloud / Qwen Team
    Score
    58.10%
    Price
    $0.30 input / $2.4 output per 1M tokens

    Strengths

    • Ranks #5 of 11 compared models
    • 60th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures NOVA-63, not total model capability

Selection summary

Best AI Models for NOVA-63

Qwen3.5-397B-A17B currently leads NOVA-63 with 59.10%. 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-Plus
Qwen3.5-122B-A10B
Qwen3.5-27B
Benchmark rank #1Qwen3.5-397B-A17B59.10% · $0.60 input / $3.6 output per 1M tokens
Benchmark rank #2Qwen3.7 Max59.00% · $2.5 input / $7.5 output per 1M tokens
Benchmark rank #3Qwen3.7-Plus58.80% · $0.50 input / $3.0 output per 1M tokens