Brutkey

Michael Westergaard
@michael@westergaard.social

there is absolutely a market other than home enthusiasts for open models. i have tons of customers that think they need to add ai to their applications, but do not wish to send their data abroad or to us big tech companies even if the models are hosted locally.

if using llms to write code was actually useful, i'd strongly argue for self-hosting a model for our developers (and optionally customers) over uploading it to github where microsoft can do whatever with it. llms can (sort of) help extracting information from documents to a structured format or aid in natural-language search, and for those purposes, i would argue for a self-hosted model over sending your internal documents to a us web-service

we can sell self-hosted models to eu customers as an eu company much better than a us company can, and we can sell that much better if the model is recognizable (gpt-oss) or at least decently working (llama) than if it is chinese (deepseek) or shit (mistral)

there is little use for open models for regular people, but there is for enterprise customers

David Gerard
@davidgerard@circumstances.run

@michael@westergaard.social wot's the running costs like?

do they tend to use a cloud or on-prem?

(i am very interested in practicalities of self-hosting this stuff, not sure how systemically important it is yet but it's the sort of thing that may well be)


Michael Westergaard
@michael@westergaard.social

Depends. Mostly cloud. More cloud providers allow hosting models and only pay per use. Of course, your data gets mixed in with others to facilitate that, and you pay per token like at OpenAI.

Other rent you a GPU, and you par per month depending on the type of GPU (which is dictated by model needs).

These are the prices from DigitalOcean (white background, US but purely in the hosting business) and Scaleway (black background, French). Typically around a dollar/euro/pound per 1M tokens for a mid-tier model or 2k/month.