For organizations handling sensitive financial, health, or user data, sending requests to public LLM services is a compliance blocker. Deploying open-weights models like **Llama 3** or **Mistral** on secure local or private cloud infrastructure ensures data never leaves corporate boundaries.

Serving Local Models with Ollama

Local serving platforms like Ollama make running open-weights models as simple as pulling an image. Developers can query it using a local API endpoint equivalent to public model interfaces.

# Running a model locally in console
ollama run llama3

# Fetching response via curl API
curl http://localhost:11434/api/generate -d '{
  "model": "llama3",
  "prompt": "Explain database indexes."
}'

Performance & Hardware

By leveraging frameworks like vLLM and TensorRT-LLM, developers achieve throughputs that rival public cloud APIs. Scaling local inference requires dedicated GPU hardware, but it eliminates ongoing API request token costs.