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multimodal benchmark

Nuscene Leaderboard

A multimodal benchmark for scene understanding and reasoning over the nuScenes autonomous driving domain.

Updated Aug 17, 2026

Models3
Model coverage3
MetricScore
EvidenceB

On this page

  • Ranking
  • Highlights
  • Distribution
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  • About
  • FAQ

Nuscene Ranking

Higher score ranks better on this benchmark.

3 rows
Columns

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Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelACQwen3.5-122B-A10BAlibaba Cloud / Qwen TeamScore15.4%Percentile100.0%Participants3EvidenceCEvaluatedAug 17, 2026
Rank02ModelACQwen3.5-27BAlibaba Cloud / Qwen TeamScore15.2%Percentile50.0%Participants3EvidenceCEvaluatedAug 17, 2026
Rank03ModelACQwen3.5-35B-A3BAlibaba Cloud / Qwen TeamScore14.6%Percentile0.0%Participants3EvidenceCEvaluatedAug 17, 2026

Nuscene Highlights

The leading models and scores on this benchmark.

Rank #1Qwen3.5-122B-A10B15.4%Rank #2Qwen3.5-27B15.2%Rank #3Qwen3.5-35B-A3B14.6%

Nuscene Score Distribution

A closer view of the leading scores on this benchmark.

Nuscene

The Top AI Models for Nuscene

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

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

  1. 01
    AC
    Qwen3.5-122B-A10BAlibaba Cloud / Qwen Team
    Score
    15.4%
    Price
    $0.40 input / $3.2 output per 1M tokens

    Strengths

    • Ranks #1 of 3 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Nuscene, not total model capability
  2. 02
    AC
    Qwen3.5-27BAlibaba Cloud / Qwen Team
    Score
    15.2%
    Price
    $0.30 input / $2.4 output per 1M tokens
    Speed
    Up to 6.7 tok/s via Novita

    Strengths

    • Ranks #2 of 3 compared models
    • 50th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Nuscene, not total model capability
  3. 03
    AC
    Qwen3.5-35B-A3BAlibaba Cloud / Qwen Team
    Score
    14.6%
    Price
    $0.25 input / $2.0 output per 1M tokens

    Strengths

    • Ranks #3 of 3 compared models
    • 0th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Nuscene, not total model capability

Selection summary

Best AI Models for Nuscene

Qwen3.5-122B-A10B currently leads Nuscene with 15.4%. 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.

Benchmark rank #1Qwen3.5-122B-A10B15.4% · $0.40 input / $3.2 output per 1M tokensBenchmark rank #2Qwen3.5-27B15.2% · $0.30 input / $2.4 output per 1M tokensBenchmark rank #3Qwen3.5-35B-A3B14.6% · $0.25 input / $2.0 output per 1M tokens

What is Nuscene?

What Nuscene measures and how its scores work.

A multimodal benchmark for scene understanding and reasoning over the nuScenes autonomous driving domain.

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

Family
Nuscene
Modality
multimodal
Primary category
multimodal
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
nuscene|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about Nuscene.

Which model scores highest on Nuscene?

Qwen3.5-122B-A10B is currently ranked first with 15.4%.

What does Nuscene measure?

A multimodal benchmark for scene understanding and reasoning over the nuScenes autonomous driving domain.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

3 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.