Your GPU Is Lying to You About Its Capacity

This article explores why production-grade LLM serving is fundamentally a memory management problem rather than a pure compute problem. Using real-world examples from GPU inference clusters, it breaks down KV cache fragmentation, PagedAttention, prefix caching, continuous batching, chunked prefill, speculative decoding, and KV cache quantization, showing how modern inference systems achieve massive throughput gains through smarter memory orchestration