Small language model (SLM)
Also: small language models, small model
A smaller language model that may fit on a phone or laptop. Its speed, skills, and privacy depend on how it is used.
Running a model on your own machine means loading all of its numbers into memory, like luggage into an overhead bin. Quantization shrinks the luggage. The graphics card’s memory (VRAM) is the bin that matters for speed.
The fuller definition
A small language model has far fewer parameters than a frontier model and can often run on a laptop or phone. It trades breadth of capability for speed, cost, and local control.
Go deeper
Idealized value storage only, in decimal GB. Metadata, caches, mixed precision, and runtime overhead add to actual requirements. This is not a GPU purchasing calculator.
A concrete example
A model with a few billion parameters extracts fields from documents on a firm laptop without sending data anywhere.
The distinction that matters
Small is relative and shifts every year. Test the specific model on the specific task rather than relying on size labels.
Related terms
Local model
A model that runs on your own computer, so your documents never leave it.
FoundationsParameter
One of the billions of adjustable numbers inside a model. Training sets them; using the model does not change them.
Hardware & hostingQuantization
Storing model numbers with less detail. This can save memory. The effect on quality depends on the model and the task.
Where it is taught
Run a local model and verify the actual setupSource and further reading
Google · Machine Learning GlossaryThe definition and example are written for this library. The link gives background, official documentation or legal authority as labelled. Legal scope depends on the jurisdiction and current text; product features depend on release and settings.