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Arena, the AI leaderboard everyone uses, is now a $100M business

Arena, the AI leaderboard platform that originated as a UC Berkeley research project, has reached $100 million in annualized run-rate revenue just eight months after launching its commercial service. The company's rapid growth is driven by its AI Evaluations service, which provides performance analytics to model labs and enterprises. Arena competes with human labeling startups like Mercor and Scale AI in the post-training refinement market.

read2 min views1 publishedJun 29, 2026
Arena, the AI leaderboard everyone uses, is now a $100M business
Image: TechCrunch AI

Just eight months after launching its commercial service, AI leaderboard provider Arena, which originated as a research project at UC Berkeley in 2023, has reached $100 million in annualized run-rate revenue.

Arena is best known for its popular crowdsourced AI model performance leaderboard, generated from over 10 million user evaluations. Its consumer website lets a user type a prompt it sends to two models; afterwards, the user chooses which model did a better job.

While Arena’s popular AI model leaderboard is free for public use, the company began generating revenue from its platform in September when it introduced AI Evaluations, a service that provides model labs and enterprises with deep-dive performance analytics gathered from its community. Arena’s rapid revenue growth shows that its commercial offerings are as popular with customers as they are with its community of evaluators, who are frequently drawn to the platform for early access to the latest, often unreleased, AI models.

“A lot of people don’t even understand that our business is making any money at all; people still see us as like an open-source project,” Anastasios Angelopoulos, Arena’s co-founder and CEO, told TechCrunch.

While Arena calls its revenue milestone ARR, a term that traditionally stood for [annualized recurring revenue](https://techcrunch.com/2026/05/22/how-vcs-and-founders-use-inflated-arr-to-kingmake-ai-startups/), Angelopoulos clarified that the company charges customers for “consumption,” which means that its revenue is not recurring.

While Arena doesn’t have direct competitors – Yupp, another crowdsourced AI model-picking startup, [shut down](https://techcrunch.com/2026/03/31/yupp-ai-shuts-down-33m-a16z-crypto-chris-dixon/) in March— Angelopoulos said the company competes “for the same dollar” with human labeling startups like Mercor, Surge, and Scale AI, all of which assist model makers in refining their AI during post-training.

As AI providers strive to maximize model performance, their appetite for post-training refinement services continues to surge. When Arena announced in January that it raised a $150 million Series A at a post-money valuation of $1.7 billion, its annualized revenue was $30 million.

Elsewhere, Handshake’s gross annualized revenue from AI training has nearly doubled since January, climbing from $550 million to nearly $1 billion, The Information reported in April. Mercor’s annualized revenue also topped $1 billion earlier this year, up from $500 million last September, according to The Information.

Arena ranks models on a variety of tasks such as text, coding, vision, and image generation, as well as complex, long-running workflows through its recently introduced Agent Mode.

Along with Angelopoulos (pictured left), Arena was co-founded by fellow UC Berkeley postdoctoral student Wei-Lin Chiang (pictured center), who serves as the startup’s CTO. The startup was also co-founded by Ion Stoica (pictured right), the renowned UC Berkeley professor and Databricks co-founder who advised the project before it incorporated as a company in April 2025.

Arena has raised a total of $250 million from investors including Felicis, Andreessen Horowitz, The House Fund, LDVP, Kleiner Perkins, Lightspeed Venture Partners, Laude Ventures, and UC Investments.

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