A vision-language browsing benchmark for multimodal web research and tool-use workflows.
As of March 2026, GLM-5V-Turbo leads the BrowseComp-VL leaderboard with 51.9% , followed by Kimi K2.5 (42.9%) and Claude Opus 4.6 (35.9%).
GLM-5V-Turbo
Zhipu AI
Kimi K2.5
Moonshot AI
Claude Opus 4.6
Anthropic
According to BenchLM.ai, GLM-5V-Turbo leads the BrowseComp-VL benchmark with a score of 51.9%, followed by Kimi K2.5 (42.9%) and Claude Opus 4.6 (35.9%). The scores show moderate spread, with meaningful differences between the top tier and mid-tier models.
3 models have been evaluated on BrowseComp-VL. The benchmark falls in the Agentic category. This category carries a 22% weight in BenchLM.ai's overall scoring system. BrowseComp-VL is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
Year
2026
Tasks
Multimodal browsing tasks
Format
Vision-language web research evaluation
Difficulty
Multimodal browser-agent
BenchLM stores BrowseComp-VL as a display-only provider-table reference while keeping BrowseComp as the weighted core browsing benchmark.
GLM-5V-TurboVersion
BrowseComp-VL 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 vision-language browsing benchmark for multimodal web research and tool-use workflows.
GLM-5V-Turbo by Zhipu AI currently leads with a score of 51.9% on BrowseComp-VL.
3 AI models have been evaluated on BrowseComp-VL on BenchLM.
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