Spatial Intelligence Benchmark

ERQA

ERQA - embodied/spatial reasoning question answering benchmark.

Category

Spatial Intelligence

Score type

percent

Scale

100%

higher is better

Models tested

13

What is ERQA?

ERQA is a benchmark for understanding where things are in space. The official description says: "ERQA - embodied/spatial reasoning question answering benchmark". Below we describe in simple words what benchmarks of this type generally examine.

What does it test?

ERQA 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: ERQA - embodied/spatial reasoning question answering benchmark.

Frequently asked questions

What is the ERQA benchmark?

ERQA is a benchmark for understanding where things are in space. The official description says: 'ERQA - embodied/spatial reasoning question answering benchmark'. Below we describe in simple words what benchmarks of this type generally examine.

What does ERQA test?

ERQA 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 ERQA score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.

Where do I get ERQA 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/erqa/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 13 models tested

Reset
# Model Score Date Source Verified
1 Qwen3.8-Flash-Next
Qwen Team (Alibaba)
72.3%
26.08.2026 Report Verified
2 Qwen3.8-27B
Qwen Team (Alibaba Cloud)
65.5%
18.08.2026 Report Verified
3 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
64.8%
01.02.2026 Report Unverified
4 Qwen3.6-27B
Qwen Team (Alibaba Cloud)
62.5%
22.04.2026 Qwen Team (official model card) Verified
5 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
62%
01.02.2026 Report Verified
6 Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
61.8%
22.04.2026 Qwen Team (official model card - comparison) Unverified
7 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
60.5%
22.04.2026 Qwen Team (official model card - comparison) Unverified
8 Gemma4-31B-it
Google
57.5%
22.04.2026 Qwen Team (official model card - comparison) Unverified
9 Qwen3.5-4B
Qwen
54%
01.02.2026 Report Verified
10 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
52.5%
01.02.2026 Report Unverified
11 LFM3-VL-2B
LiquidAI
48.2%
— Report Verified
12 d1-2B
LiquidAI
45.8%
— LiquidAI/d1-2B model card (performance table) Unverified
13 LFM3-Omni-2B
LiquidAI
38.5%
— Report Verified

What now?

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