Small Language Models are Gaining Popularity Due to Accessibility and Efficiency

Updated on November 13, 2024

Small Language Models (SLMs) are gaining popularity compared to advanced large language models (LLMs). It offers the same efficiency and accessibility as LLMs.

“Small Language Models are small AI generative models that can process and generate human language. They can be trained by accessing online text data or information.”

According to Forbes, “LLMs and SLMs are pals and not opponents.” While large language models run on powerful computer servers. For example, ChatGPT is powered by extensive online text data. SLMs provide similar functionality in a more compact form easily conducted on smartphones and other devices without stable internet access. However, rather than competitions both are required to stimulate different works.

Advantages of Small Language Models

SLMs are cost-effective compared to LLMs. Preferably, they are less expensive and consume less energy.
SLMs are well-suited to protect your data as they work in private cloud environments.
SLMs can work in local servers which enhances their performance and response time.
SLMs are easily accessible as they don’t require specialized multiple GPUs.
SLMs are faster to train than LLMs because they demand less computational power and data.

As a result, Small Language Models are restricted to applications with limited resources such as mobile apps, AI customer service, and real-time data analysis.

Thankfully, evolving technology can also practice to compress LLM capabilities into smaller models similar to SLMs. More advanced features are introduced to improve the efficiency of SLMs. The words “small” and “large” are now only for the dictionary, both language models are developing over time.

Charu Thakur

Expertise