AI Development
A language model small enough to run on a consumer device with low latency, in practice usually under about 10 billion parameters.
A language model small enough to run on a consumer device with low latency, in practice usually under about 10 billion parameters. Microsoft's Phi-3 report showed a 3.8B model could rival Mixtral 8x7B and GPT-3.5 on benchmarks while still fitting on a phone. NVIDIA researchers argue SLMs should be the default inside agentic systems, because agents repeat a narrow set of tasks where cost and latency matter more than broad conversation.
Primary source: arxiv.org
Example
In practice, developers reach for Small Language Model (SLM) when they need the capability described above as part of an AI feature or workflow.
Hands-on guides, comparisons, and tutorials that cover AI Development.
FAQ
A language model small enough to run on a consumer device with low latency, in practice usually under about 10 billion parameters.
Small Language Model (SLM) sits in the AI Development part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Developers Digest publishes tutorials and videos that cover AI Development topics including Small Language Model (SLM). Check the blog and YouTube channel for hands-on walkthroughs.
Related
Empirical relationships showing that a language model's loss falls as a predictable power law as you increase parameters, training data, and training compute.
A model card is a short document published with a trained machine learning model that explains its intended uses, its limitations, and how it performs across different conditions and groups.
Sycophancy is when a model tells users what they want to hear instead of the accurate answer, for example by agreeing with their stated views or backing down when they push back.

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