Choorai
Lv.4 · Inference

Local LLM

Local LLMs are useful for cost, privacy, offline workflows, and faster experiments. Start with Ollama for local tests and compare vLLM when GPU-server throughput matters.

Decide this first

Before running a model, define which feature and quality criteria it must pass. Without a harness, model switching becomes subjective.

Ollama Quick Experiment

terminal
ollama pull llama3.1
ollama run llama3.1

curl http://localhost:11434/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama3.1",
    "messages": [{ "role": "user", "content": "hello" }]
  }'

vLLM Server Experiment

terminal
vllm serve meta-llama/Llama-3.1-8B-Instruct \
  --host 0.0.0.0 \
  --port 8000

curl http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meta-llama/Llama-3.1-8B-Instruct",
    "messages": [{ "role": "user", "content": "hello" }]
  }'

Selection Criteria

Ollama

Good for personal development, quick model swaps, and local Mac/Linux tests.

vLLM

Good for GPU servers, OpenAI-compatible serving, and throughput comparison.

Hosted API

Good for current model quality, operational reliability, and fast product validation.

Gateway

Useful when you need base URL switching and routing policies across models.

Next Actions

Last updated: June 22, 2026 · Version: v0.0.1

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