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reasoning benchmark

CountBench Leaderboard

CountBench evaluates object counting capabilities in visual understanding.

Updated Sep 5, 2026

Models7
Model coverage7
MetricScore
EvidenceB

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  • Ranking
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CountBench Ranking

Higher score ranks better on this benchmark.

7 rows
Columns

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Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelACQwen3.5-27BAlibaba Cloud / Qwen TeamScore0.98 pointsPercentile100.00%Participants7EvidenceCEvaluatedSep 8, 2026
Rank02ModelACQwen3.5-35B-A3BAlibaba Cloud / Qwen TeamScore0.98 pointsPercentile83.33%Participants7EvidenceCEvaluatedSep 8, 2026
Rank03ModelACQwen3.6-27BAlibaba Cloud / Qwen TeamScore0.98 pointsPercentile66.67%Participants7EvidenceCEvaluatedSep 8, 2026
Rank04ModelACQwen3.6 PlusAlibaba Cloud / Qwen TeamScore0.98 pointsPercentile50.00%Participants7EvidenceCEvaluatedSep 8, 2026
Rank05ModelACQwen3.5-122B-A10BAlibaba Cloud / Qwen TeamScore0.97 pointsPercentile33.33%Participants7EvidenceCEvaluatedSep 8, 2026
Rank06ModelACQwen3 VL 235B A22B ThinkingAlibaba Cloud / Qwen TeamScore0.94 pointsPercentile16.67%Participants7EvidenceCEvaluatedSep 8, 2026
Rank07ModelCONorth Micro Vision InstructCohereScore0.73 pointsPercentile0.00%Participants7EvidenceCEvaluatedSep 8, 2026

CountBench Highlights

The leading models and scores on this benchmark.

CountBench Score Distribution

A closer view of the leading scores on this benchmark.

CountBench

The Top AI Models for CountBench

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

What is CountBench?

What CountBench measures and how its scores work.

CountBench is a benchmark for evaluating object counting capabilities in visual understanding.

It measures object counting capabilities in visual understanding using Score, reported in points.

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

Family
CountBench
Modality
image
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 CountBench.

Which model scores highest on CountBench?

Qwen3.5-27B is currently ranked first with 0.98 points.

What are the top three models on CountBench?

The current leaders are Qwen3.5-27B (0.98 points), Qwen3.5-35B-A3B (0.98 points), and Qwen3.6-27B (0.98 points).

Which CountBench 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 CountBench 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 CountBench measure?

It measures object counting capabilities in visual understanding using Score, reported in points.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

7 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 #1Qwen3.5-27B0.98 points
Rank #2Qwen3.5-35B-A3B0.98 points
Rank #3Qwen3.6-27B0.98 points
Rank #4Qwen3.6 Plus0.98 points

Ranking basisThis countbench 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
    Qwen3.5-27BAlibaba Cloud / Qwen Team
    Score
    0.98 points
    Price
    $0.30 input / $2.4 output per 1M tokens

    Strengths

    • Ranks #1 of 7 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures CountBench, not total model capability
  2. 02
    AC
    Qwen3.5-35B-A3BAlibaba Cloud / Qwen Team
    Score
    0.98 points
    Price
    $0.25 input / $2.0 output per 1M tokens

    Strengths

    • Ranks #2 of 7 compared models
    • 83th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures CountBench, not total model capability
  3. 03
    AC
    Alibaba Cloud / Qwen Team
    Score
    0.98 points
    Price
    $0.60 input / $3.6 output per 1M tokens

    Strengths

    • Ranks #3 of 7 compared models
    • 67th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures CountBench, not total model capability
  4. 04
    AC
    Alibaba Cloud / Qwen Team
    Score
    0.98 points
    Price
    $0.50 input / $3.0 output per 1M tokens

    Strengths

    • Ranks #4 of 7 compared models
    • 50th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures CountBench, not total model capability
  5. 05
    AC
    Alibaba Cloud / Qwen Team
    Score
    0.97 points
    Price
    $0.40 input / $3.2 output per 1M tokens

    Strengths

    • Ranks #5 of 7 compared models
    • 33th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures CountBench, not total model capability

Selection summary

Best AI Models for CountBench

Qwen3.5-27B currently leads CountBench with 0.98 points. 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.

Qwen3.6-27B
Qwen3.6 Plus
Qwen3.5-122B-A10B
Benchmark rank #1Qwen3.5-27B0.98 points · $0.30 input / $2.4 output per 1M tokens
Benchmark rank #2Qwen3.5-35B-A3B0.98 points · $0.25 input / $2.0 output per 1M tokens
Benchmark rank #3Qwen3.6-27B0.98 points · $0.60 input / $3.6 output per 1M tokens