Choose by workload
Ollama manages and runs supported models locally; vLLM is an inference serving engine with an OpenAI-compatible API option. Test the exact model, hardware, client, context, and concurrency.
Measure target hardware
Benchmark realistic prompts, output length, queueing, memory, accelerator use, and failure behaviour. Average throughput hides peak latency.
Control the API
Use controlled ingress, caller authentication, request limits, model registers, and trusted secrets. A reachable port is not an internal-service boundary.
Version runtime and models
Record model, licence, runtime, driver, image, parameters, test result, and rollback point. Change one studied boundary at a time.
Comparison
Compare deployment work.
| Area | Ollama | vLLM |
|---|---|---|
| Focus | Local model workflow | Serving engine. |
| API | Compatible clients | OpenAI-compatible server option. |
| Both | Test model and hardware | Test model and hardware. |
Questions
Which is faster?
Benchmark the chosen workload.
Is local safe by default?
No; control callers and data.
What proves readiness?
Load, access, and quality tests.
Selection
Check model and client.
Measure target hardware.
Review capacity and releases.
Checks
Keep evidence.
Model register
Versions are recorded.
Load test
Envelope is measured.
Access test
Callers are controlled.
