Vitalik: The intersection between Ethereum infrastructure and AI is constantly expanding, and models need to be optimized for relevant use cases.

CoinFeed reported on May 28th that Vitalik Buterin shared the latest progress on his Autonomous Large Language Model (LLM) setup, noting the expanding intersection between Ethereum infrastructure and AI. He mentioned the release of Deepseek V4, whose 2-bit quantized version can run within 90GB of memory, achieving speeds of approximately 35 tokens/second on Apple hardware but only about 7 tokens/second on AMD. He emphasized that true support for multiple hardware vendors is key to distinguishing "decentralized AI" from "CROPS AI." Furthermore, Mistral's Leanstral model (focused on Lean code writing) can run within 70GB, achieving performance comparable to a 1TB parameter large model.