multimodal benchmark
CountQA Leaderboard
CountQA is a multimodal benchmark for visual object counting and quantity reasoning over images.
Updated Sep 5, 2026
Models1
Model coverage1
MetricScore
EvidenceB
CountQA Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score77.00% | Percentile100.00% | Participants1 | EvidenceC | Evaluated |
CountQA Highlights
The leading models and scores on this benchmark.
The Top AI Models for CountQA
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis countqa AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01ACAlibaba Cloud / Qwen Team
- Score
- 77.00%
- Price
- $0.50 input / $3.0 output per 1M tokens
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures CountQA, not total model capability
Selection summary
Best AI Models for CountQA
Qwen3.7-Plus currently leads CountQA with 77.00%. 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.
What is CountQA?
What CountQA measures and how its scores work.
CountQA is a benchmark for visual object counting and quantity reasoning over images.
It measures visual object counting and quantity reasoning over images, reported as a Score ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- CountQA
- Modality
- multimodal
- Primary category
- multimodal
- 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 CountQA.
Which model scores highest on CountQA?
Qwen3.7-Plus is currently ranked first with 77.00%.
What are the top three models on CountQA?
The current leaders are Qwen3.7-Plus (77.00%).
Which CountQA model has the lowest official input price?
Qwen3.7-Plus has the lowest matched official input price at $0.50 input / $3.0 output per 1M tokens.
Which models are fastest among CountQA 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.