February 22, 2026
The most expensive mistake in local LLM adoption is running a 70B model for a task that a 3B model handles at 20x the speed for equivalent quality. The second most expensive mistake is running a 3B model on a task that requires 32B-level reasoning and getting garbage output.
Matching model size to task complexity is the core skill. This guide provides a framework grounded in empirical benchmarks, not marketing claims.
February 22, 2026
Performance problems discovered in production are expensive. A service that handles 100 requests per second in dev might collapse at 500 in production because connection pools exhaust, garbage collection pauses compound, or a downstream service starts throttling. Load testing reveals these limits before users do.
Load testing answers specific questions: What is the maximum throughput before errors start? At what concurrency does latency degrade beyond acceptable limits? Can the system sustain expected traffic for hours without resource leaks? Will a traffic spike cause cascading failures?