Ethereum co-founder Vitalik Buterin has drawn a sharper line on what “decentralized AI” should mean, arguing that real user sovereignty and privacy require models that run across a range of actual hardware. In a recent update, Buterin pointed to a concrete benchmark: DeepSeek V4’s 2-bit quantized version fits within about 90 GB of VRAM and delivers roughly 35 tokens per second on Apple hardware versus 7 tokens per second on AMD. Those numbers, while modest on the AMD side, show that a capable AI model can operate locally without a data center—a core requirement for his newly articulated CROPS AI concept (Consequential, Recoverable, Open, Private, and Sovereign AI).
Buterin’s framing cuts through the hype around token-incentivized compute marketplaces and on-chain AI agents. He insists that if an AI model can’t run on the mid-tier hardware that ordinary users and Ethereum node operators already have, it fails the privacy test. The performance gap between Apple silicon and AMD also underscores a hardware fragmentation problem the ecosystem must solve for local AI to become mainstream.
The update links this hardware test to Ethereum’s privacy infrastructure. Buterin envisions a hybrid system where zero-knowledge proofs verify remote LLM calls and private RPC reads shield user metadata, preventing node operators from snooping on transactions. He also called for more Ethereum-tuned AI models that understand Solidity and smart contract security, which could become powerful auditing tools. The overall message is a multi-year infrastructure vision, not a short-term market narrative. Still, the DeepSeek V4 numbers prove that a useful locally-running AI model is no longer a distant goal.
