Venice: Privacy by Default

As the usefulness of LLMs continues to accelerate, the conversation is beginning to shift from model capability to control.

Who owns the model? Who can read the conversation? Who decides what the model is permitted to say? As frontier AI systems become embedded in daily personal and work life (software development, legal advice, financial planning, relationship advice, etc.) these questions are emerging front and center. For most commercial AI products today, the answer is to harvest as much user data as possible.

Venice AI, founded in May 2024 by Erik Voorhees, is building the alternative, sovereign AI. A decentralized AI inference network where conversations are never logged and no centralized entity can censor model outputs or access user prompts. In an environment where AI regulation is accelerating globally and users are becoming acutely aware of what they surrender when they type into a chatbot, Venice’s timing could not be better. The conversation around privacy in AI needs to be had, and Venice is the main player driving it.

The Product

Similar to multi-model platforms like Perplexity, Venice is a model aggregator which supports text, image, code, and video generation models including Qwen, LLaMA, Dolphin Mistral, DeepSeek, and Flux. Instead of training its own models, Venice hosts frontier and open source models for users, enabling private access to both traditional and uncensored models within a zero-retention architecture. These are available via web interface or API.

Venice carries unique appeal for a wide variety of users including those doing sensitive professional work, living somewhere with surveillance concerns, or simply philosophically opposed to feeding their data to large tech companies. User growth trajectory has gone parabolic with over 2 million registered users and more than 1 million API calls per day from developers as of April 2026. Based on registered user growth trends, we estimate Venice currently has upwards of 150k daily active users.

The adoption of Venice as the de facto private LLM platform has been accelerated by the launch and airdrop of VVV in January 2025, the infrastructure utility token.

How VVV Token Fits into the Puzzle

As we have stated across multiple articles, the novelty of tokens is now dead. In past cycles, tokens could simply live adjacent to the projects that launched them without any economic alignment to protocol growth. Now, they need to have an actual purpose beyond simply existing. Crypto-native projects are now frequently asked to justify the existence of their token. It is a fair question, and one we ask ourselves daily when evaluating projects. Many tokens exist primarily to enable fundraising, with utility bolted on at a later date. VVV does not fall into that category.

Compute Use-Case:

Venice offers a free and pro tier for $18/month. Pro users get unlimited chat queries and 1,000 API credits. For power users such as developers and AI agents, staking VVV gives the same benefits plus a proportional share of Venice's total API inference capacity, in perpetuity, at zero marginal cost per request. For example, staking 1% of all VVV entitles the holder to 1% of total capacity indefinitely, functioning like a perpetual access license. In addition, stakers also earn emissions-based yield, currently 18%. VVV can be staked at any time and has a 7-day unstaking period.

Diem:

In August 2025, Venice launched DIEM, a secondary token that deepens the economic architecture. Minting DIEM requires stakers to lock their sVVV into a separate contract redeemable 1-1 for sVVV at any point. While inference capacity for sVVV depends on proportional ownership of the staking pool, DIEM allows powers users to predictably budget their inference capacity while creating liquidity for the tradable DIEM tokens. One DIEM staked delivers $1 of Venice API access every day, in perpetuity.

VVV Buybacks:

Since November 2025, a portion of the platform revenue derived from Pro subscriptions and API usage has been used to purchase VVV on the open market and permanently remove it from circulation. The first confirmed on-chain burn was executed on December 10, 2025. Monthly burns have continued since, with the total burnt amount from the buy-and-burn program equating to 161,968 VVV tokens in 4 months.

Token Emissions:

As with most crypto projects, VVV emissions started high for sVVV holders and are being dramatically reduced over time to balance demand/dilution dynamics. The emissions schedule has been cut three times: from 14 million at launch, to 8 million annually in February 2025 (a 43% reduction), and to 6 million annually in February 2026 (a further 25% cut). Venice announced they are slashing emissions another 50% by July 1st, down to 3m annually. Once monthly burns exceed approximately 250,000 VVV per month after the July emissions cut the protocol will flip net deflationary, a stated goal for the Venice team.

Team Alignment (AI & Crypto’s Intersection)

CEO and co-founder Erik Voorhees self-funded Venice with no VC backing on a mission to address rising concerns around centralized AI products’ threats to individual privacy and autonomy. Erik founded ShapeShift in 2014, which became one of the most widely used non-custodial crypto exchanges before its transition to a DAO. Voorhees has been a consistent, credible voice for individual financial sovereignty for more than a decade. He has been vocal about the threat that the current suite of AI infrastructure poses to individual privacy, and has oriented Venice's product development explicitly around addressing it.

Where This Goes

The broader shift underway in AI has less to do with capability and more to do with trust. As models become more embedded in consequential decisions, the question of who controls AI infrastructure will move from policy circles into mainstream conversation, accelerated by data breaches, censored outputs, and growing public awareness of how commercial AI systems handle user data. Regulatory pressure is already building across the EU AI Act, US executive orders, and Congressional hearings on model transparency. That narrative tailwind is structural and does not depend on crypto market conditions to materialize. 

If Venice becomes the default infrastructure layer for private AI inference, the place where individuals, developers, and enterprises route queries they cannot afford to have read, stored, or censored, the demand for VVV as the settlement and coordination asset for that network is unbounded by its current user count. The 2 million users of early 2026 are not the ceiling. They are the proof of concept.

That said, the thesis is not self-fulfilling. Venice still needs to prove that user growth can persist, that private inference remains a differentiated category, and that growing platform usage actually translates into durable demand for VVV rather than simply attention around the network. Competition is coming from every direction, from open-source model hubs to other privacy-oriented interfaces, and token systems rarely play out exactly as designed. Emissions, staking, and buybacks can support the architecture, but their long-term significance depends on real economic throughput, not optics. Liquidity, holder concentration, and regulatory shifts also remain part of the equation. The opportunity is clear, but so are the execution requirements.

This article is for informational purposes only and does not constitute investment advice.