Introducing Dedicated Container Inference: Delivering 2.6x faster inference for custom AI models

Together's Dedicated Container Inference is a specialized solution designed to optimize production-grade orchestration for custom AI models, particularly those requiring GPU-intensive workloads. Unlike traditional inference platforms that focus on a single abstraction, Together offers a flexible, container-based framework that allows users to run custom inference code in production without building their own orchestration layer, addressing needs such as autoscaling, queuing, traffic control, and monitoring. This approach supports diverse workloads, including video generation and avatar synthesis, by enabling multiple independent queues, policy-driven traffic control, and predictable behavior during demand spikes. Together's platform facilitates seamless transitions from model training to deployment, minimizing operational overhead and enhancing model performance through hands-on optimization. By allowing teams to focus on building products rather than managing clusters, it delivers substantial speed and cost efficiencies, making previously uneconomical models viable for production.