Venice AI’s rapid revenue expansion has pushed renewed attention toward VVV, the token linked to the privacy-focused AI inference platform. The debate intensified after Yan Liberman, managing partner at Delphi Ventures and co-founder of Delphi Digital, published a detailed May 19 X post arguing that Venice is one of crypto AI’s most underappreciated revenue stories. Liberman disclosed that he holds the token discussed and has a direct financial interest in its performance.
Venice ARR Acceleration Draws Market Attention
Venice positions itself as a privacy-first AI inference platform that lets users access frontier and open-source models without identifying themselves to the underlying model provider. Liberman’s thesis centers on Venice’s combination of anonymous proxying, open-source model routing, hardware-attested TEE inference and end-to-end encrypted inference inside one consumer product, with the privacy mode selectable per request. That architecture, he wrote, is what separates Venice from conventional “private AI chat” products.
“The business has been growing meaningfully. Most Crypto Twitter discussion of Venice understates current revenue, recent growth, and the forward trajectory. Venice recently started publishing daily subscriber data, and three weeks of granular data show a clear acceleration in new subscription ARR additions.”
The numbers cited in the post have sharpened market focus on VVV. Liberman estimates Venice’s current total ARR at roughly $55 million to $65 million, with a midpoint near $60 million. He builds that figure from an estimated 3 million signups as of May 16, about 150,000 active paying subscribers, roughly $33 million in subscription ARR and an estimated $25 million to $30 million in API ARR. The token’s price action has added to the attention: VVV is up 970% since Jan. 1 and 24.22% over the last seven days, ranking fourth behind HYPE, Nexus and Zcash.
API revenue is the key variable in the revenue acceleration case. Liberman argues that new API run-rate has recently been tracking subscription monthly recurring revenue at roughly a one-to-one ratio, supported by developer integrations and rising usage. Daily token throughput rose from 20 billion in early February to more than 60 billion in early May, while the paid subscriber base increased by about 50% over the same period, leading him to attribute much of the throughput increase to API workloads rather than subscribers alone.
“API revenue is the harder piece to size since it isn’t directly disclosed. My base case is that new API run-rate has been added at approximately 1:1 with new subscription MRR recently, with historical additions running below that ratio. The result is a current API ARR base that is meaningful but somewhat below subscription ARR, narrowing toward parity over time.”
VVV Valuation Debate Turns on API Revenue
At $14 per token, Liberman calculates VVV at about a $660 million market capitalization and roughly $1.12 billion fully diluted valuation. On his estimated $60 million current ARR base, that implies approximately 11 times revenue on market cap and 19 times on FDV. If Venice sustains around $200 million of annualized ARR additions, the 12-month forward ARR estimate rises to about $260 million, compressing those multiples to roughly 2.5 times revenue on market cap and 4.3 times on FDV.
“Current ARR sits at approximately $60M, being added to at an annualized rate of approximately $200M and accelerating. On current ARR, VVV trades at roughly 11x revenue (19x FDV), a discount to private inference peer OpenRouter at 26x. On a 12-month forward ARR of approximately $260M ($60M current base plus $200M of annualized additions), VVV trades at roughly 2.5x revenue (4.3x FDV).”
The comparison with OpenRouter is central but not straightforward. Liberman describes OpenRouter as the closest business-model analog among private inference platforms, while noting that OpenRouter’s revenue likely carries higher gross margins because it operates as an aggregator and does not bear the same underlying compute costs. Venice, by contrast, charges customers directly and pays for underlying inference, which Liberman estimates gives it lower gross margins, in the 40% to 60% range. That means the valuation debate is not only about ARR growth, but also about how much of that revenue converts into durable token value.
VVV’s token structure adds another layer. Total supply is listed at 79.93 million VVV, with 46.03 million circulating and about 70% of circulating supply staked. Venice has cut emissions several times and uses revenue-linked buy-and-burn mechanics, though Liberman says recurring burns remain modest today. DIEM, a separate token launched in August 2025, represents tokenized API access, with each DIEM granting $1 of Venice API credit per day indefinitely.
“One caveat worth flagging is that VVV is a token, while the OpenRouter, Fireworks, and Together AI multiples reference equity. Investors in those private companies typically own securities with residual economic claims, governance and information rights, and in many cases liquidation preferences. VVV holders do not own equity in Venice, do not have a legal claim on company cash flows or exit proceeds, and cannot force revenue distribution.”
The risk side of the debate is also explicit. Liberman points to hyperscalers adding privacy features, local inference becoming easier for mainstream users, and competition from Brave, DuckDuckGo, Proton’s Lumo, Maple, Tinfoil, NEAR and Phala as factors that could pressure Venice’s standalone market. He also emphasizes that VVV is not equity, even if it trades as a liquid proxy for Venice’s growth.
The market’s focus on VVV now rests on whether Venice can sustain its current ARR addition pace and whether API revenue continues to scale alongside subscriptions. Liberman’s case presents Venice as a differentiated privacy AI platform with rapidly improving revenue metrics, but the valuation argument depends heavily on forward growth, token mechanics and the durability of Venice’s edge as privacy-focused inference becomes more competitive.
AI Transparency Note: This article was prepared with the assistance of an AI system based on the sources listed and was reviewed, edited, and approved by a human editor before publication. All quotes, data points, and factual claims are intended to be grounded in the cited source material; however, errors cannot be ruled out entirely.
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