Spatial Intelligence Benchmark

LingoQA

LingoQA - spatial and linguistic reasoning benchmark for visual grounding.

Category

Spatial Intelligence

Score type

percent

Scale

relative

higher is better

Models tested

5

What is LingoQA?

LingoQA is a benchmark for understanding where things are in space. The official description says: "LingoQA - spatial and linguistic reasoning benchmark for visual grounding". Below we describe in simple words what benchmarks of this type generally examine.

What does it test?

LingoQA measures understanding where things are in space. In detail, it checks:

  • locating and pointing to regions in images
  • reasoning about positions, counts and relations between objects
  • 3D-aware questions such as depth, perspective and room layout
  • grounded perception tasks that must stay anchored to pixel locations

How to read the score

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: LingoQA - spatial and linguistic reasoning benchmark for visual grounding.

Frequently asked questions

What is the LingoQA benchmark?

LingoQA is a benchmark for understanding where things are in space. The official description says: 'LingoQA - spatial and linguistic reasoning benchmark for visual grounding'. Below we describe in simple words what benchmarks of this type generally examine.

What does LingoQA test?

LingoQA mainly measures understanding where things are in space. Concretely, it checks: locating and pointing to regions in images; reasoning about positions, counts and relations between objects; 3D-aware questions such as depth, perspective and room layout.

How is the LingoQA score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Where do I get LingoQA data and scores?

The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/lingoqa/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 5 models tested

Reset
# Model Score Date Source Verified
1 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
82%
01.02.2026 Report Unverified
2 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
80.8%
01.02.2026 Report Verified
3 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
79.2%
01.02.2026 Report Unverified
4 Qwen3.5-4B
Qwen
74.4%
01.02.2026 Report Verified
5 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
66.8%
01.02.2026 Report Unverified

What now?

You've seen how models score on LingoQA — here's what to do next.