Groq Performance Tuning

Overview

Maximize Groq's LPU inference speed advantage. Groq already delivers extreme throughput (280-560 tok/s) and low latency (<200ms TTFT), but client-side optimization -- model selection, prompt size, streaming, caching, and parallelism -- determines whether your application fully exploits that speed.

This skill walks through six tuning levers at a high level; the complete, copy-pasteable code for each lives in references/implementation.md, and end-to-end worked scenarios live in references/examples.md.

Prerequisites

• Groq API key — set GROQ_API_KEY in the environment. The groq-sdk client (new Groq()) reads it automatically; never hardcode the key.
• Node.js 18+ with the groq-sdk package installed (npm install groq-sdk).
• Optional packages for the caching and parallelism steps: lru-cache and p-queue (npm install lru-cache p-queue).
• A baseline latency measurement of your current integration so you can confirm the tuning actually helps.

Groq Speed Benchmarks