Launch HN: Design Arena (YC S25) – Head-to-head AI benchmark for aesthetics

74 points by grace77 ↗ HN
Hi HN, I’m Grace from Design Arena (https://www.designarena.ai/) - we’re building a crowdsourced benchmark for AI-generated visuals (websites, images, video, and more). We put AI models and builder tools in head-to-head comparisons that get voted on by real users from around the world. Think “Hot or Not” for the AI era :)

(Btw, when we say real users we mean real users, so you may get a captcha on the site. Sorry, but we have to use every bot protection available! We only want human ratings, for obvious reasons.)

Here’s a demo video: https://www.youtube.com/watch?v=vPyEQnuVgeI

We didn’t set out to build this - we were actually working on an AI game engine. But we found that models sucked at look-and-feel. Even when the output code was usually functional, most visual aspects lacked the soul that makes great graphics feel alive.

So we built a this-or-that game, just for ourselves, to figure out which generated outputs had the best graphics. To our surprise, that turned out to be more exciting than the original idea—it turns out this is a widespread problem! We did a Show HN a month ago (https://news.ycombinator.com/item?id=44542578) and that was partly what convinced us to make this benchmark thing our actual product.

State-of-the-art models might be winning IMO gold, but they are still putting white text on a white background. There needs to be some measurement of what’s good and what isn’t (yes, there is such a thing as good design!), and it sure isn’t going to come from LLMs.

We come from engineering backgrounds (Apple and Nvidia) with a love for design; we know when we like or dislike something, even when we can’t say why. This-or-that / hot-or-not games are made for domains like this: Design Arena’s goal is to make everything stupidly simple so humans can just do the easy part: like-vs.-dislike. Which also turns out to be the valuable part, because what’s easiest for humans is actually the part that the AIs can’t currently do.

Since our Show HN, we’ve extended our initial set of ~25 LLM models to 54 LLM models, 12 image models, 4 video models, 22 audio models, and 22 vibe-coding tools (like Lovable, Bolt, v0, Firebase Studio, and more). In this last category, we’ve been surprised to find that agentic tools that were not specifically marketed as vibe-coders like Devin performed exceedingly well in the builder category, outperforming dedicated builder tools like Lovable, v0, and Bolt.

Our users are mostly devs who want to spin up a frontend, or designers who want to spin up design variants faster. In both cases, Design Arena provides a quick way to find out which options are better than others. Dev-or-designer needs to make the final calls, because there’s no substitute for good judgment. But this type of formatting can really help.

We plan to make money by offering version testing as a service to companies that need to quantify improvements in their product between builds.

This is the first time we’ve ever worked on something like this! We’d love to learn from you all and look forward to your feedback.

12 comments

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Cool - do you train model that will be the proxy from the votes of persons?
Is this an area that is not yet covered by other user rating benchmark sites like LLMarena?
Curious if you guys got into YC for this idea or something else?
AI is terrible at making nice looking design layout with font selections.

Sure it can make great looking images but nothing can make a nice looking poster or basic page layout.

I’m waiting for someone to solve this. I’m not even sure it takes AI it might just be programmatic.

Great concept — definitely needed and will hopefully push the labs to improve design abilities of models!
This is interesting but, speaking frankly, I see many seemingly insurmountable issues. Here are some:

- Contests will often be won not by the entry that best adhered to the prompt, but the best-looking one. This happened in the contest "Input Prompt Build a brutalist website to a typeface maker," which I got as a recent example. The winning entry had megawatt-bright magenta and yellow, which shouldn't appear anywhere near brutalism, and in other design aspects had almost no connection to brutalism either -- but it was the most attractive of the bunch.

- The approach only gets you to a local maximum. Current LLMs aren't very good designers, as you say, so contests will involve picking between mostly middling entries. You'd want a design that's, say, a 9 or a 10 on a 10-point scale -- but some 95% of the entry distribution will probably be between 5.5 and 7.5 or so, and that's what users will get to pick from.

This is actually really needed, current ai design tools are so predictable and formulaic, like every output feels like the same purple gradients with rounded corners and that one specific sans serif font that every model seems obsessed with, it's gotten to the point where you can spot ai-generated designs from a mile away because they all have this weird sterile aesthetic that screams "made by a model"
Can you write what you imagine is a good “game dev” prompt?
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Hmm idk about the focus on aesthetics. GPT image is your top image model, a model which is famously poor on aesthetics (though excellent on prompt adherence). I admit it's a difficult thing to eval, though, as in most side by side comparisons users will always pick the image with better prompt adherence regardless of instructions.
What incentive is there for real users to continuously evaluate models for you for free?