Ollama excels for prototyping and low-concurrency local LLM development with its simple setup and developer experience, but struggles under concurrent load due to sequential request handling. vLLM uses PagedAttention and continuous batching to deliver 20x higher throughput at 50 concurrent users, making it the production choice when serving 10+ concurrent users. The transition point is 5-15 concurrent users depending on latency requirements. Both expose OpenAI-compatible APIs, enabling straightforward migration by changing base URL and model name configuration.
Table of contents
Table of ContentsWhat Ollama Actually Does (and Does Well)What vLLM Actually Does (and Why It Exists)The Benchmark: Single User vs. 50 Concurrent UsersFeature-by-Feature ComparisonThe Transition Point: A Decision Framework for StartupsMigration Path: Ollama to vLLM Without Rewriting Your AppWhat About the Alternatives?Scale When the Numbers Tell You ToSort: