Crawling the web models that run on 64 GB
2 models with published weights that fit in 64 GB — a workstation. Counted at four-bit quantisation, weights only, leaving the machine about a third of its memory and a gigabyte for context: room for roughly 67 billion parameters. A mixture of experts is counted in full, because it is held in full even though only a few experts compute.
A workstation, or a well-specified Mac. Seventy-billion-parameter models fit at four-bit, which is the class where local output stops being obviously worse than the hosted models people pay for. Loading takes real time and the machine will be warm.
Tools that fetch pages and hand them back as something a model can read: rendered HTML, markdown, a screenshot, a whole site map. Priced per page or per session. The differences that matter are whether JavaScript is executed, what happens at a login or a bot check, and how gracefully the thing fails on a site that does not want to be read.
- xlm-roberta-largeFacebook AI community0.6B≈0.4 GB at 4-bit
- xlm-roberta-baseFacebook AI community0.3B≈0.2 GB at 4-bit