Multimodal · Benchmark profile
A visual detection and grounding benchmark slice used to compare zero-shot object understanding across diverse domains.
Data verified 27 Jul 2026 · Methodology 1.8.0
Benchmark score on ODINW13
Qwen3.7-Plus leads at 51.1%, followed by Qwen3.6-35B-A3B (50.8%).
2 ranked models · higher is better · labels show rank and score
| Model | Rank | Provider | Score |
|---|---|---|---|
| Qwen3.7-Plus | #1 | Alibaba Cloud | 51.1% |
| Qwen3.6-35B-A3B | #2 | Alibaba Cloud | 50.8% |
One best score per model · higher is better
| Rank | Model | Provider | License | Evidence use | Score |
|---|---|---|---|---|---|
| #1 | Qwen3.7-Plus qwen3.7-plus | Alibaba Cloud | closed | Reference only | 51.1% |
| #2 | Qwen3.6-35B-A3B qwen3-6-35b-a3b | Alibaba Cloud | open | Estimated reference | 50.8% |
About ODINW13
A visual detection and grounding benchmark slice used to compare zero-shot object understanding across diverse domains. Results stay tied to the exact model variant and evaluation system. Multiple systems for the same model use the best published score on this page; overall Lumina scoring uses the median of ranking-eligible rows.
Open benchmark source ↗FAQ
A visual detection and grounding benchmark slice used to compare zero-shot object understanding across diverse domains.
Qwen3.7-Plus by Alibaba Cloud currently leads with 51.1%.
2 models in the LuminaBench cohort have a qualifying score on this benchmark.
No. This benchmark is display-only and does not enter the overall Lumina composite.
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