This reporting page isolates visual reasoning and image understanding from the broader multimodal category. It prioritizes sourced benchmarks for diagrams, grounding, counting, real-world image QA, and multimodal math.
This page ranks models using only sourced image-understanding benchmarks in the reporting family.
Bottom line: Image understanding spans 13 benchmarks but sourced coverage is still sparse. MMMU-Pro is the best single signal — check the multimodal leaderboard for ranked models.
According to BenchLM.ai, Nemotron 3 Nano Omni 30B A3B leads this ranking with a score of 84.6, followed by Qwen3.6-27B (81.7) and Qwen3.6-35B-A3B (80.6). There is meaningful separation between the top models, suggesting genuine performance differences.
All models in this ranking are open-weight, meaning they can be self-hosted for maximum control and cost efficiency.
This ranking is based on provisional overall weighted scores across BenchLM.ai's scoring formula tracked by BenchLM.ai. For detailed model profiles, click any model name below. To compare two specific models head-to-head, use the "vs #" links.
Nemotron 3 Nano Omni 30B A3B
NVIDIA · 256K
Qwen3.6-27B
Alibaba · 262K
Qwen3.6-35B-A3B
Alibaba · 262K
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The top model on this sourced reporting-family slice is Nemotron 3 Nano Omni 30B A3B by NVIDIA with an average of 84.6.
The best open-weight model is Nemotron 3 Nano Omni 30B A3B at position #1.
4 models are listed with sourced benchmark coverage in this reporting family.
This is a reporting family ranking, not a weighted category. It averages sourced image understanding and visual reasoning benchmarks to give a focused view of this capability.
Models must have sourced results on at least a quarter of the benchmarks in this family to be included. Coverage varies — a model with 2 benchmark scores is less reliable than one with 5.
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