multimodal benchmark
PointGrounding Leaderboard
PointGrounding is a multimodal benchmark for evaluating language-guided pointing capabilities in vision-language models across diverse reasoning scenarios.
Updated Sep 5, 2026
Models1
Model coverage1
MetricScore
EvidenceB
PointGrounding Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score66.50% | Percentile100.00% | Participants1 | EvidenceC | Evaluated |
PointGrounding Highlights
The leading models and scores on this benchmark.
The Top AI Models for PointGrounding
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis pointgrounding 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
- 66.50%
- Price
- $0.10 input / $0.40 output per 1M tokens
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures PointGrounding, not total model capability
Selection summary
Best AI Models for PointGrounding
Qwen2.5-Omni-7B currently leads PointGrounding with 66.50%. 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 PointGrounding?
What PointGrounding measures and how its scores work.
PointGrounding is a benchmark based on PointArena's Point-Bench, a curated dataset of approximately 1,000 pointing tasks across five categories: Spatial, Affordance, Counting, Steerable, and Reasoning.
It measures language-guided pointing using the Score metric, reported as a ratio, across positional references, functional part identification, attribute-based grouping, relative pointing, and open-ended visual inference.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- PointGrounding
- 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 PointGrounding.
Which model scores highest on PointGrounding?
Qwen2.5-Omni-7B is currently ranked first with 66.50%.
What are the top three models on PointGrounding?
The current leaders are Qwen2.5-Omni-7B (66.50%).
Which PointGrounding model has the lowest official input price?
Qwen2.5-Omni-7B has the lowest matched official input price at $0.10 input / $0.40 output per 1M tokens.
Which models are fastest among PointGrounding 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.