Show HN: DesignArena – crowdsourced benchmark for AI-generated UI/UX
designarena.aiI’ve been using AI to generate some repetitive frontend (guilty), and while most outputs felt vibe-coded, some results were surprisingly good. So I cleaned it up and made a ranking game out of it with friends, and you can check it out here: https://www.designarena.ai/vote
/vote: Your prompt will be answered by four random, anonymous models. You pick the one you prefer and crown the winner, tournament-style.
/leaderboard: See the current winning models, as dictated by voter preferences.
/play: Iterate quickly by seeing four models respond to the same input and pressing space to regenerate the results you don’t lock-in.
We were especially impressed with the quality of DeepSeek and Grok, and variance between categories (To judge by the results so far, OpenAI is very good for game dev, but seems to suck everywhere else).
We’ve learned a lot, and are curious to hear your comments and questions. Excited to make this better!
This is really good! It would be really cool to somehow get human designs in the mix to see how the models compare. I bet there are curated design datasets with descriptions that you could pass to each of the models and then run voting as a "bonus" question (comparing the human and AI generated versions) after the normal genAI voting round.
wow this is a super interesting idea, and the team loves it — we'll fast follow-through and follow-up here when we add it, thanks for the suggestion!
This would be extra interesting for unique designs - something more experimental, new. As as for now even when you ask AI to break all rules it still outputs standard BS.
As a UX/UI designer in Korea, I love seeing related products being released. I hope they become even more advanced in the future.
This is a surprisingly good idea. The model vs model is fun, but not really that useful.
But this could be a legitimate way to design apps in general if you could tell the models what you liked and didn't like.
yes! that is the hope — /play is our first attempt at building out utility, would love your feedback and will ship hard to make it happen!
How about adding "mobile"? A lot of the time models tend to default to designs that don't make sense on mobile, even when instructed to design it as such.
Really? When I have a system prompt 'mobile-first design' it 100/100 works perfectly. What sort of things are you trying?
I tried the vote and both results always suck, there's no option to say neither are winners. Also it seems from the network tab you're sending 4 (or 5?) requests but only displaying the first two that respond, which biases it to the small models that respond more quickly which usually results in showing two bad results
Yes — great point. We originally waited for all model responses and randomized the vote order, but that made it a very bad user experience -- some models, especially open-source ones, took over 4 minutes to respond, leading to a high voter drop-off rate.
To preserve the voter experience without introducing bias, our current approach waits for the slowest model within each binary comparison — so even if one model is faster, we don’t display until both are ready. You're right that this does introduce some bias for the two smallest models, and we'd love to hear suggestions for how to make this better!
As for the 5th request: we actually kick off one reserve model alongside the four randomly selected for the tournament. This backup isn’t shown unless one of the four fails — it’s not the fastest or lowest-latency model, just a randomly selected fallback to keep the system robust without skewing results.
Adding a "neither is good" option would improve data quality by preventing forced choices between two poor designs.
this is a great note — will be sure to add!
interesting idea, this benchmark maps fairly closely to the types of output I typically ask LLMs to generate for me day-to-day
nice! Training models using reward signals for code correctness is obviously very common; I'm very curious to see how good things can get using a reward signal obtained from visual feedback
As are we, seems like the natural next step
It would lend credibility to publish your system prompt.
System prompts can be found here: https://www.designarena.ai/system-prompts (also linked on about page).
Very cool! Can the code and design that is generated be used?
yes! we have a copy code and copy react code button on https://www.designarena.ai/play
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I wish—just added them back
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thank you! posting now :)
Thanks !!