A practical comparison of Ollama and vLLM for local LLM inference in 2026 — covering continuous batching, PagedAttention, throughput benchmarks, and a decision framework to pick the right engine for your workload.
In 2026, running LLMs locally on your own machine is no longer a niche pursuit — it's a practical, cost-effective alternative to cloud APIs. This guide covers hardware requirements, Ollama setup, model selection, and development integrations for developers who want full control over their AI stack.
Why did my local AI build a Snake game that couldn't collide and a Dino that couldn't jump? I pitted 9B local models against DeepSeek V4 Flash to see if "local-first" is ready for prime time. The result: a masterclass in why reasoning depth beats privacy every single time.
The idea was simple: run a capable, private AI assistant with GPU acceleration and a clean web interface. In reality, it turned into a deep dive into agent systems, model limitations, and performance tuning.