hyperlakeDiscuss a deployment ↗
Videos · · 2:23

Continuous Batching   How AI APIs Serve Thousands of Users at Once

Continuous batching schedules LLM requests one token step at a time, improving GPU utilization, throughput, and latency under concurrent AI API demand.

In the full article

  1. What is continuous batching in LLM inference?
  2. How does iteration-level scheduling work?
  3. How does continuous batching improve throughput and latency?
  4. What causes prefill-decode interference?
  5. Key takeaways
  6. How Hyperlake helps
  7. Frequently asked questions

Start with a workload. Build the environment around it.

Explore example deployments, or see how the platform assembles, deploys, governs and operates the stack.