Vinit Vyas

Feb 16, 2026150 min readfoundation

LLM Inference: From Black Box to Production

A ground-up explanation of LLM inference, from black box to production optimizations. Covers tokenization, attention, KV cache, memory bottlenecks, batching, PagedAttention, quantization, and more. No code, just diagrams and TinyLlama as our running example.

inference transformers attention kv-cache memory fundamentals vllm optimization batching quantization production

Posts tagged “memory”

LLM Inference: From Black Box to Production