Gradient AI by DigitalOcean

Gradient AI by DigitalOcean's main purpose is to run AI applications reliably in production. It ensures predictable performance, sustainable economics, and simple operation processes.

Gradient AI optimizes Agentic Inference workloads by providing an inference-optimized AI infrastructure. This includes an intuitive inference cloud that combines inference-optimized computing power, managed software, and a full-stack cloud built to scale, allowing for efficient workload management.

Gradient AI provides a robust infrastructure that is specially designed for AI applications. This includes an inference-optimized compute, managed software, full-stack cloud, and direct GPU access. The infrastructure design aims to yield higher throughput and lower cost per token.

Higher throughput in Gradient AI refers to the ability to process a larger number of tasks or transactions simultaneously without compromising on performance. This is enabled by its inference-optimized infrastructure and robust computation capabilities.

In Gradient AI, 'Cost per Token' refers to the cost associated with the processing of each individual unit-of-work in an AI application or process. The exact calculation mechanism of 'Cost per Token' is not explicitly described on their website.