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Design an LLM Inference Platform is a hard system design interview question covering GPU scheduling, KV cache, continuous batching, streaming — the kind asked at FAANG (Facebook/Meta, Apple, Amazon, Netflix, Google) and AI-first companies like Anthropic, OpenAI, and Nvidia.
Design a production platform to serve large language models. The system should handle millions of inference requests per day with low latency and high throughput, supporting both streaming and batch use cases.
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Design rounds are decided on capacity estimates. Both tools are free.
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What each one means, and how interviewers probe it.
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A full interview loop is more than one round. These are the others, each with what is on the site for it.