Compare · Building
Local LLM vs API
Same idea — next-token prediction — different ops reality. Pick based on privacy, latency budget, and whether you can eval quality honestly.
Quick comparison
- Local — data stays closer to you; hardware caps model size; you own uptime and updates.
- API — frontier quality and scale; per-token cost; vendor retention and rate limits matter.
- Hybrid — local for drafts/PII scrubbing; API for hard steps after redaction.
When local wins
Sensitive prototypes, air-gapped experiments, and learning how local LLMs feel under quantization. Start with Ollama or LM Studio, then run golden tasks.
When APIs win
Hard reasoning, multimodal edges, and products that need elastic capacity. Still pin versions, log traces, and verify — see What is an LLM?.
FAQ
Is local always more private?
Local inference keeps prompts on your machine if you configure it that way — but apps, plugins, and telemetry can still leak. Read the tool’s network behavior.
Which is better quality?
Hosted frontier APIs usually win on hard reasoning today. Local models win on privacy, offline use, and predictable unit cost once hardware is paid for.