Vitalik Buterin wants to reroute AI through Ethereum

Vitalik Buterin wants to stop the AGI arms race and reroute AI through Ethereum cryptocurrency.

In a post on X, Vitalik Buterin rejected the framing of “working on AGI” as if it were a finish line.

He argued that chasing artificial general intelligence as a competitive milestone ignores the harder questions about values, power, and long term impact.

Instead of racing to build bigger centralized models, he called for AI systems rooted in decentralization, privacy, verification, and human empowerment.

His outline reads like a manifesto for merging AI with Ethereum infrastructure.

First, he wants private and trustless AI interaction. That means local large language models running on personal devices instead of corporate clouds, paired with zero knowledge payments and client side verification of outputs.

Second, he sees Ethereum as the economic layer for AI to AI activity, covering API payments, bot hiring, security deposits, and on chain dispute resolution.

Third, he imagines local AI assistants that audit smart contracts and verify proofs without relying on centralized platforms.

Fourth, he points to governance tools like upgraded prediction markets and quadratic voting to coordinate AI systems.

The disruption behind the news: Buterin is attacking the business model of frontier AI head on.

Today, training a frontier model costs north of 100 million dollars in compute and energy.

High cost and inefficiencies is one of the 5 signs an industry is ripe for disruption.

Inference is centralized because it has to be.

The capital intensity locks power inside a handful of companies.

If AGI becomes the organizing goal, the advantage compounds. The biggest balance sheets win.

Buterin’s counter is not philosophical. Move inference to the edge. Use crypto rails for payments and coordination. Replace trust in model providers with cryptographic verification.

If even 5 percent of global LLM usage shifted to local models over the next 24 months, that would redirect billions in cloud revenue. There are over 6 billion smartphones in circulation. If only 1 percent of them ran a lightweight local model for daily tasks, that is 60 million edge AI nodes. That is a distribution channel no single AI lab controls.

For crypto, this is existential. Ethereum needs high value transaction volume beyond speculation. AI to AI payments, escrow deposits, and machine level contracts could generate consistent on chain activity that is not driven by meme cycles. If bots are paying bots in microtransactions 24 hours a day, that is durable demand for block space and for ETH as a settlement asset.

For regulators, this flips the risk profile. Centralized AGI labs are easy targets. A decentralized mesh of local models and on chain coordination is harder to license, tax, or shut down. That tension will not stay theoretical.

What to watch next?

Watch the hardware curve.

If consumer devices can run 7B to 13B parameter models smoothly within 18 months, local AI becomes viable at scale. Apple, Qualcomm, and Nvidia will matter more than OpenAI in that scenario.

Watch zero knowledge tooling.

If verification costs drop below a few cents per transaction, developers will actually use it. If it stays expensive and slow, this vision stalls.

Watch whether serious AI startups integrate Ethereum wallets and on chain settlement by default. If that happens, crypto starts becoming AI infrastructure.

The race to AGI assumes the biggest systems will win through scale. Buterin believes design matters more than size. If he’s right, the next wave won’t be controlled by massive data centers, but by those who reroute AI through Ethereum, putting control in the hands of the users.