ODInW13
ODInW13 - object detection in the wild across 13 domains.
Category
Spatial Intelligence
Score type
percent
Scale
100%
higher is better
Models tested
5
What is ODInW13?
ODInW13 is a benchmark for understanding where things are in space. The official description says: "ODInW13 - object detection in the wild across 13 domains". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
ODInW13 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: ODInW13 - object detection in the wild across 13 domains.
Frequently asked questions
What is the ODInW13 benchmark?
ODInW13 is a benchmark for understanding where things are in space. The official description says: 'ODInW13 - object detection in the wild across 13 domains'. Below we describe in simple words what benchmarks of this type generally examine.
What does ODInW13 test?
ODInW13 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 ODInW13 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 ODInW13 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/odinw13/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Model scores 5 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
|
50.8%
|
16.04.2026 | Qwen Team (official model card) | Verified |
| 2 |
Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
|
44.5%
|
01.02.2026 | Report | Verified |
| 3 |
Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
|
43.2%
|
01.02.2026 | Report | Unverified |
| 4 |
Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
|
42.6%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |
| 5 |
Qwen3.5-27B
Qwen Team (Alibaba Cloud)
|
41.1%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |