Local inference consists of running an AI model directly on your own hardware —computer, server, or mobile device— instead of sending requests to an external provider's cloud. The entire calculation phase, from the moment you enter an input until you get a response, occurs on your equipment without the data ever leaving it.
This matters for three main reasons:
- Privacy: sensitive information never leaves your machine, which is critical in sectors such as healthcare or the legal field.
- Cost: you avoid paying for API usage, which is cost-effective for high volumes.
- Availability: it works without an internet connection and you do not depend on the latency or outages of a remote service.
In practice, tools like Ollama or LM Studio allow running open models (for example, Llama or Mistral) on a laptop. The nuance is the hardware: large models require a lot of RAM or VRAM memory, so locally, smaller or quantized versions are usually used.