Inference Performance: Loading, First Tokens, Decoding, and Throughput
Break requests into measurable stages and explain how concurrency, caching, and batching affect waiting time.
Break requests into measurable stages and explain how concurrency, caching, and batching affect waiting time.
A practical guide to choosing a local inference engine by model format, hardware fit (Apple Silicon included), context settings and security.
Follow a token through MoE routing to distinguish total parameters, active parameters, memory, speed, load balancing, and communication.
Check how to turn on speculative decoding in a local runtime, then work through probability correction and timing examples to see when it really speeds things up, and compare chains, trees, and self-speculation.