Microsoft released in April 2024 Phi-3 mini, the first among three small language models (SLMs) the company plans to release.

SLMs are compact versions of LLMs. Phi-3 mini is an SLM that has 3.8 billion parameters, and is trained on a much smaller dataset, as compared to GPT-4.

It supports a context window of up to 1.28 lac tokens.

The company will add more models including Phi-3 small and Phi-3 medium to the Phi-3 family.

These models are cost-effective to operate and perform better on smaller devices such as laptops and smartphones.

SLMs are fine-tuned and are customized for specific tasks. They undergo targeted training (less computing power and energy consumption).

After receiving the prompt, the time taken by a model to make predictions is called inference latency. SLMs process quickly as they are smaller in size. They are more responsive and are suitable for real-time applications.

According to Microsoft, Phi-3 mini has outperformed models of the same size and next size across a variety of benchmarks (language, reasoning, coding, math).

It is ideal for analytical tasks as Phi-3 mini has strong reasoning and logic capabilities.