Lab L12 · Platform

Fit the Model

  • Launch lab
  • MVP set
  • ≈ 45 min
  • Interactive version coming

A light 3D server view. GPU memory fills with weights, KV cache and overhead as you change the model, precision, context length and batch.

What you’ll practise

  1. Computing KV-cache bytes per token, including the grouped-KV trap
  2. Choosing tensor parallelism and precision so a 70B-class model fits with headroom
  3. Checking latency targets with a simulated benchmark and writing the capacity memo

In the book