AI Fundamentals

Small Language Model (SLM)

A compact language model (typically ≤ 10B parameters) optimized for on-device inference, low-latency use cases, or cost-sensitive high-volume workloads. Examples: Phi-4, Gemma 3, Llama 3.2 1B/3B. Increasingly capable — some SLMs match 2024-era mid-tier LLMs on narrow tasks.

Related terms

Large Language Model (LLM)
A type of AI model trained on vast amounts of text data to understand and generate human-like text. Examples include GPT-4, Claude, and Llama. LLMs power many GenAI applications.
Foundation Model
A large pre-trained model (LLM, vision, or multimodal) intended as a general-purpose substrate that downstream apps consume via prompting, fine-tuning, or agent scaffolding. Under the EU AI Act these are General-Purpose AI (GPAI) models and their providers carry specific obligations.

Framework dimensions

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LLM Model Comparison

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LLM Cost Optimization Patterns

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Where this fits

Small Language Model (SLM) is part of the AI Fundamentals vocabulary used in the Generative AI Maturity Framework. See the full glossary for the complete set of 149 defined terms, or take the free maturity assessment to see where your organisation stands.