A grounded visual QA benchmark focused on answering practical questions about real-world images and scenes.
BenchLM mirrors the published score view for RealWorldQA. Qwen3.6-35B-A3B leads the public snapshot at 85.3% , followed by Qwen3.6-27B (84.1%) and LFM2.5-VL-450M (58.4%). BenchLM does not use these results to rank models overall.
Qwen3.6-35B-A3B
Alibaba
Qwen3.6-27B
Alibaba
LFM2.5-VL-450M
LiquidAI
The published RealWorldQA snapshot is tightly clustered at the top: Qwen3.6-35B-A3B sits at 85.3%, while the third row is only 26.9 points behind. The broader top-10 spread is 26.9 points, so the benchmark still separates strong models even when the leaders cluster.
3 models have been evaluated on RealWorldQA. The benchmark falls in the Multimodal & Grounded category. This category carries a 12% weight in BenchLM.ai's overall scoring system. RealWorldQA is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
Year
2026
Tasks
Real-world visual question answering
Format
Image-grounded QA
Difficulty
General visual reasoning
RealWorldQA is useful because it emphasizes practical perception and grounded answering on realistic images rather than synthetic or purely academic multimodal tasks.
Version
RealWorldQA 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
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.
A grounded visual QA benchmark focused on answering practical questions about real-world images and scenes.
Qwen3.6-35B-A3B by Alibaba currently leads with a score of 85.3% on RealWorldQA.
3 AI models have been evaluated on RealWorldQA on BenchLM.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.