Insights from a Global Survey: How AI Models Perform in UI/UX and Coding Tasks
In recent months, the landscape of AI-powered design and development tools has become increasingly vibrant, thanks to a dynamic community of users and developers. To better understand how leading AI models perform in UI/UX design and coding, I launched a comprehensive, crowdsourced benchmarking initiative. This open-source project invites users worldwide to generate and compare websites, games, 3D models, and data visualizations across various AI platforms. The results, gathered from nearly 4,000 votes and over 5,000 participants, shed light on current capabilities and future potential.
Establishing a Benchmark Community
I developed a platform called DesignArena.ai, where users can perform “one-shot” generation of diverse digital assets using different AI models. Participants evaluate and vote on the quality, speed, and usability of these outputs. This transparency aims to foster a community-driven understanding of AI’s role in creative and technical workflows.
Key Findings from the Survey
- Leading Models for Coding and Design: Claude and DeepSeek
The leaderboard reveals that Claude—specifically the Opus variant—and DeepSeek models excel in generating both UI/UX designs and code. Claude was the most favored by users, likely owing to its balanced capabilities and user-friendly interface. DeepSeek models, particularly v0, demonstrate especially strong performance in website generation, although their slower processing speeds can be a bottleneck. For developers prioritizing rapid iteration, Claude remains a practical choice for implementing interfaces efficiently.
- The Underrated Power of Grok 3
Among lesser-known but highly effective models, Grok 3 stands out as a hidden gem. Despite less online visibility—possibly due to associations with Elon Musk—Grok 3 consistently ranks within the top five in quality. Notably, it offers faster performance compared to many of its rivals, making it an attractive option for both design and coding tasks.
- Variability in Gemini 2.5-Pro’s Performance
The Gemini 2.5-Pro model presents a mixed picture. Some users report excellent UI/UX outputs, while others find its results less consistent. The variability suggests that its effectiveness may depend on the specific task or prompt, highlighting the importance of nuanced prompt engineering when working with this model.
- **OpenAI’s GPT and Meta’s Llama
