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In this episode, we break down the key differences between Large Language Models (LLMs) and Small Language Models (SLMs). While LLMs like GPT-4 dominate with broad capabilities and massive datasets, SLMs are emerging as lightweight, cost-efficient alternatives optimized for specific tasks and edge deployments. We explore their use cases, trade-offs in accuracy vs. speed, and how enterprises can choose the right model based on context, control, and cost. Whether you’re building AI at scale or deploying on-device assistants, this episode helps you navigate the evolving landscape of language models.
5
33 ratings
In this episode, we break down the key differences between Large Language Models (LLMs) and Small Language Models (SLMs). While LLMs like GPT-4 dominate with broad capabilities and massive datasets, SLMs are emerging as lightweight, cost-efficient alternatives optimized for specific tasks and edge deployments. We explore their use cases, trade-offs in accuracy vs. speed, and how enterprises can choose the right model based on context, control, and cost. Whether you’re building AI at scale or deploying on-device assistants, this episode helps you navigate the evolving landscape of language models.
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