Svmuu News Vitalik Buterin published an article sharing his localized, privatized LLM deployment plan up to April 2026. The core objective is to prioritize privacy, security, and autonomous control, minimizing opportunities for remote models and external services to access personal data. It aims to reduce risks of data leaks, model jailbreaks, and malicious content exploitation through methods such as local inference, local file storage, and sandbox isolation.
Regarding hardware, he tested solutions including a laptop equipped with an NVIDIA 5090 GPU, an AMD Ryzen AI Max Pro 128 GB unified memory device, and DGX Spark, using Qwen3.5 35B and 122B models for local inference. Among these, the 5090 laptop achieved approximately 90 tokens/s with the 35B model, the AMD solution about 51 tokens/s, and DGX Spark about 60 tokens/s. Vitalik stated that he prefers building a local AI environment based on high-performance laptops, while utilizing tools such as llama-server, llama-swap, and NixOS to establish the overall workflow.