How DistilLabs is Delivering 50% Lower Inference Costs with Production-Grade Autoscaling on Cerebrium

Distil Labs, a developer platform for building task-specific small language models with high accuracy, faced challenges in maintaining cost-effective and scalable infrastructure for model deployment and inference. To address these challenges, they partnered with Cerebrium, which provided a comprehensive platform solution that enabled dynamic scaling, optimized cold starts, and competitive pricing. This partnership allowed Distil Labs to focus on improving their models and customer value, while Cerebrium handled the infrastructure needs, including autoscaling and global deployment capabilities. As a result, Distil Labs achieved significant improvements in inference cost and model accuracy, while maintaining consistent latency and reliability, allowing them to handle high-traffic periods effectively. The collaboration with Cerebrium also fostered a highly responsive and integrated working relationship, further enhancing Distil Labs' operational efficiency.