Serve Qwen3.8-2.4T-A95B, a 2.4T-Parameter Model, with Configurable Reasoning on NVIDIA GB300 NVL72
Source
Michelle Horton
Author
Michelle Horton
Published
Terms in this piece · Glossary
open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
mixture-of-experts — A model built from many specialist sub-networks where only a few activate per token, giving big-model capability at small-model running cost.
inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.
Why it matters
A near-frontier open weightsA model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.Full definition → model with published serving guidance is a real option for teams that want to run inferenceRunning a trained model to get answers — the phase where AI is actually used, as opposed to trained.Full definition → themselves instead of renting an API.
