Why Simulate Before You Scale¶
Deploying large language models in production is one of the most expensive infrastructure decisions an organization can make. A single high-end GPU costs upwards of $30,000, and a production cluster can run into millions per year. Yet most teams make their first scaling decisions based on rough estimates, vendor benchmarks, or — worst of all — trial and error on live hardware.
What if you could test your deployment plan before spending a dollar on GPUs?
Cross-posted from the BLIS blog
This post was originally published on the BLIS blog.