Unlocking the Power and Limits of AI in UI/UX and Coding: Insights from a Global Study
In the rapidly evolving world of Artificial Intelligence, understanding how different models perform in real-world applications is crucial for developers and designers alike. Recently, I conducted a comprehensive survey involving over 6,000 participants worldwide to evaluate various AI models’ capabilities in UI/UX design and coding tasks. The findings offer valuable perspectives on which AI tools stand out and where improvements are still needed.
A Collaborative Benchmark for AI Performance
Over the past few months, I have actively developed a crowdsourced benchmarking platform—DesignArena—that enables users to generate websites, games, 3D models, and data visualizations from different AI models. This platform allows for side-by-side comparisons, helping the community identify the most effective tools for specific creative and technical needs.
With nearly 4,000 votes from approximately 5,000 active users, the platform’s data provides insightful analytics into AI performance across various domains. Here’s a summary of the key takeaways from the research:
Top Performers in UI/UX and Coding
Leading the leaderboard are models like Claude and DeepSeek. Users have expressed a clear preference for Claude Opus, which consistently delivers strong outputs in both design and coding tasks. DeepSeek models, especially version 0, perform exceptionally well—particularly in website development—but their slower processing speeds can be a drawback, making Claude a more efficient choice for interface-focused projects. Interestingly, Grok also emerged as a dark horse, demonstrating promising capabilities that deserve attention.
Noteworthy Insights on Emerging Models
Grok 3 stands out as an underrated contender. Despite limited online visibility—partly due to the controversial profile of its backer, Elon Musk—it ranks confidently within the top five and outperforms many peers in speed, offering faster results without sacrificing quality.
Complexities in Model Performance
When examining Gemini 2.5-Pro, results are more mixed. While some users report excellent UI/UX outputs, others note that the model occasionally generates poorly designed applications. Nonetheless, its ability to handle business logic remains impressive, highlighting the nuanced strengths of each model.
Challenges Facing Industry Giants
OpenAI’s GPT models tend to fall in the mid-range, delivering decent results but lacking consistency in UI/UX design. Conversely, Meta’s Llama models lag significantly behind competitors, which perhaps explains their aggressive recruitment efforts of AI talent amid substantial investments—aims to
