Home AI and development paths: a single Tesla V100 32GB in 2026

The author explores the potential of using a server-grade Tesla V100 GPU with 32GB of VRAM for running local neural networks in 2026. Despite its age, the card remains a viable solution for enthusiasts due to its large memory capacity, which allows for running models with up to 30 billion parameters natively, and up to 120 billion parameters using quantization techniques. The article details the process of building a home server and presents performance test results. The author notes that many initial conclusions regarding inference speed were flawed due to measurement inaccuracies. This piece serves as a practical guide for those seeking budget-friendly ways to deploy powerful LLMs at home, emphasizing the importance of proper hardware configuration and accurate testing to obtain objective performance data.