Small Language Models
Last Updated on February 5, 2025 by Editorial Team
Author(s): Lalit Kumar
Originally published on Towards AI.

This member-only story is on us. Upgrade to access all of Medium.
If you are not a Medium member, you can read this article here.
Large language models have become very popular recently due to the amazing capabilities shown by these models. Their applicability to automate coding, text generation has shown vast potential and applicability across various domains. But these models currently have many limitations due to their requirements of memory, processing power, storage and energy. This is why LLMs mostly are deployed on cloud platforms like AWS, Google cloud or Azure.
These limitations have led researchers to look for solutions which enables deployment of language models of devices with lesser specs like personal computers or mobile devices. One of the popular areas of research in this field is SLM i.e. .
A Small Language Model is a language model with number of parameters limited to millions to few billions. Basically, these are the models which can run on an edge devices like mobile phones, industrial equipments or in car controls. The focus of these models is to enable effective Edge AI [Read more about Edge AI in my other article here].
Think about the less powerful phones, the kind that struggle with… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.