From Scaling Laws to Cluster Size: A Practical Guide to Planning Large-Scale Model Training
Why Capacity Planning Is the Hardest Part of Large Model Training Before you write a single line of training code, you must answer a few brutal questions: How many tokens do I actually need? What sequence length should I train on? How many GPUs will this take? How long will it run? What parallelism strategy makes this feasible? Most teams get this wrong — not because they lack theory, but because they never connect scaling laws → systems constraints. ...