How do you choose an output token limit for LLM inference?
A smaller output cap can save tokens while making more answers unusable. Compare caps against task acceptance criteria before choosing one.
A smaller output cap can save tokens while making more answers unusable. Compare caps against task acceptance criteria before choosing one.
From about $300 for a 1B model to tens of millions for a frontier run. The GPU-hour formula, real published runs and worked costs at H100 list rates.
Most of an H100's cost is memory and packaging, and demand outruns supply. Three levers cut what you pay per finished job, with a worked 8-GPU example.
Run an LLM locally when it fits your memory and data must stay put; use the cloud for 70B+ models, fine-tuning and batch jobs. Break-even math inside.