Ollama vs vLLM vs llama.cpp: Which Wins for Your Use Case

#localllmdeployment #vllm #ollama #llamacpp

The 47x Throughput Gap That Changed My Deployment Strategy

Here's a number that stopped me cold: vLLM processes 47 concurrent requests while llama.cpp handles exactly one. Same model, same GPU, wildly different architectures. Most "local LLM deployment" guides treat these three tools as interchangeable. They're not. Picking the wrong one doesn't just cost performance — it can blow your entire project timeline.

I've deployed all three in different contexts: a hobbyist chatbot, a batch document processor, and a multi-user API. Each time, the "best" tool was different. The frameworks solve fundamentally different problems, and understanding those differences saves weeks of refactoring.