A multimodal coding benchmark for turning visual designs into working frontend implementations.
As of March 2026, GLM-5V-Turbo leads the Design2Code leaderboard with 94.8% , followed by Kimi K2.5 (91.3%) and Claude Opus 4.6 (77.3%).
GLM-5V-Turbo
Zhipu AI
Kimi K2.5
Moonshot AI
Claude Opus 4.6
Anthropic
According to BenchLM.ai, GLM-5V-Turbo leads the Design2Code benchmark with a score of 94.8%, followed by Kimi K2.5 (91.3%) and Claude Opus 4.6 (77.3%). The scores show moderate spread, with meaningful differences between the top tier and mid-tier models.
3 models have been evaluated on Design2Code. The benchmark falls in the Multimodal & Grounded category. This category carries a 12% weight in BenchLM.ai's overall scoring system. Design2Code is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
Year
2026
Tasks
Design-to-code tasks
Format
Visual input to frontend implementation
Difficulty
Multimodal coding
BenchLM stores Design2Code as a display-only screenshot-to-code reference rather than a weighted multimodal ranking input.
GLM-5V-TurboVersion
Design2Code 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 multimodal coding benchmark for turning visual designs into working frontend implementations.
GLM-5V-Turbo by Zhipu AI currently leads with a score of 94.8% on Design2Code.
3 AI models have been evaluated on Design2Code on BenchLM.
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