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Users can compare AI model answers from ChatGPT, Claude, Gemini, Grok, DeepSeek, and Llama.
The fundraising also attracted participation from multiple angel investors including Google Chief Scientist Jeff Dean, Twitter co-founder Biz Stone and Pinterest co-founder Evan Sharp.
Payments on the platform are provided by the likes of Stripe, PayPal, and Coinbase.
Yupp, an AI startup leveraging crypto rails to reward users for comparing answers from different AI models, has emerged from stealth with a $33 million seed round led by A16z crypto, the investment arm of Andreessen Horowitz venture capital, which focuses on crypto projects.
Yupp said the fundraising closed last year and has since been building in stealth mode over the past six months.
According to the announcement, the funding also attracted participation from Coinbase Ventures and multiple angel investors including Google Chief Scientist Jeff Dean, Twitter co-founder Biz Stone, Pinterest co-founder Evan Sharp, Perplexity CEO Aravind Srinivas, Cred CEO Kunal Shah and Coinbase CLO Paul Grewal.
Yupp said in a blog post on Friday that its platform features “over 500 models and counting: from ChatGPT and Claude to Gemini and DeepSeek, from Grok and Llama to unheard-of text and image models.
According to Yupp co-founder and CEO Pankaj Gupta, the AI startup leverages payment services from Stripe, PayPal, and Coinbase to reward users for their input in comparing answers and providing feedback on different AI models.
Users can convert some of their credits to money in USD, Euro, and 20+ other currencies, Gupta said. The company has also integrated stablecoins on Base Ethernet L2 and Solana blockchains, enabling “instant payments” via crypto rails.
The company also announced the beta launch of the Yupp VIBE (Vibe Intelligence BEnchmark) Score, an AI leaderboard that ranks AI models based on aggregated feedback from users around the world interacting with Yupp.
The company also published a separate blog post explaining how the leaderboard works. According to the post, the overall VIBESCORE of an AI model is determined by a variety of factors, including confidence interval, speed, latency, and cost, among others.
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