Vision & Language Benchmark

V-Star

V* - visual agent benchmark evaluating visual search and grounding capabilities.

Category

Vision & Language

Score type

percent

Scale

100%

higher is better

Models tested

12

What is V-Star?

V-Star is a benchmark for understanding images combined with text. The official description says: "V* - visual agent benchmark evaluating visual search and grounding capabilities". Below we describe in simple words what benchmarks of this type generally examine.

What does it test?

V-Star measures understanding images combined with text. In detail, it checks:

  • answering questions about images (figures, photos, charts, memes)
  • reading text inside images and connecting it to the question
  • visual reasoning such as counting, locating and comparing objects
  • combining what is seen with general knowledge

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: V* - visual agent benchmark evaluating visual search and grounding capabilities.

Frequently asked questions

What is the V-Star benchmark?

V-Star is a benchmark for understanding images combined with text. The official description says: 'V* - visual agent benchmark evaluating visual search and grounding capabilities'. Below we describe in simple words what benchmarks of this type generally examine.

What does V-Star test?

V-Star mainly measures understanding images combined with text. Concretely, it checks: answering questions about images (figures, photos, charts, memes); reading text inside images and connecting it to the question; visual reasoning such as counting, locating and comparing objects.

How is the V-Star 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 V-Star 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/v-star/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 12 models tested

Reset
# Model Score Date Source Verified
1 Kimi K2.6
Moonshot AI
96.9%
23.08.2026 Report Verified
2 Qwen3.6-27B
Qwen Team (Alibaba Cloud)
94.7%
22.04.2026 Qwen Team (official model card) Verified
3 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
93.7%
22.04.2026 Qwen Team (official model card - comparison) Unverified
4 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
93.2%
01.02.2026 Report Verified
5 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
92.7%
01.02.2026 Report Unverified
6 Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
90.1%
22.04.2026 Qwen Team (official model card - comparison) Unverified
7 Kimi K2.5
Moonshot AI
86.9%
23.08.2026 Report Verified
8 LFM3-VL-2B
LiquidAI
86.4%
— Report Verified
9 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
85.9%
01.02.2026 Report Unverified
10 Qwen3.5-4B
Qwen
84.3%
01.02.2026 Report Verified
11 d1-2B
LiquidAI
76.4%
— LiquidAI/d1-2B model card (performance table, "V*") Unverified
12 Gemma4-31B-it
Google
67%
22.04.2026 Qwen Team (official model card - comparison) Unverified

What now?

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