Why Small Language Models Are the Future
Less compute, more utility
Small models (under 1B parameters) run efficiently on consumer hardware. They’re faster, cheaper to deploy, and often sufficient for targeted tasks like summarization or Q&A.
The edge advantage
Deploying on-device eliminates latency and privacy concerns. For many applications, a 70M-parameter model is indistinguishable from a 7B one in practical use.
When to go big
Large models still dominate for open-ended generation or complex reasoning. But the sweet spot for production is shifting—toward models that balance capability with efficiency.