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BenchLM

MStar

We show this table for reference; we do not rank on it.

Data verified 34 confirmed releases in the last 30 daysFollow model changes

A general visual question-answering benchmark used in provider tables for real-image reasoning quality.

Benchmark score on MStar — September 27, 2026

We compile the MStar rows from provider self-reports. Qwen3.6-27B leads the table at 81.4%. We do not use these results to rank models overall.

1 modelMultimodal & GroundedCurrentDisplay onlyUpdated September 27, 2026

Benchmark score table (1 model)

Score
1
Qwen3.6-27BAlibaba · Open weight
81.4%

About MStar

Year

2026

Tasks

Real-image visual QA

Format

Image-grounded QA

Difficulty

General visual reasoning

MStar sits between broad multimodal reasoning and grounded VQA. It is useful for checking whether a model can answer real-image questions without the stronger domain structure of office or academic benchmarks.

Freshness and provenance

Version

MStar 2026

Refresh cadence

Quarterly

Staleness state

Current

Question availability

Public benchmark set

CurrentDisplay only

BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.

Questions

What does MStar measure?

A general visual question-answering benchmark used in provider tables for real-image reasoning quality.

Which model scores highest on MStar?

Qwen3.6-27B by Alibaba currently leads with a score of 81.4% on MStar.

How many models are evaluated on MStar?

1 AI models have been evaluated on MStar on BenchLM.

Last updated: September 27, 2026 · BenchLM version MStar 2026

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