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Open weights are certainly something that is very eagerly being adopted in some companies. It's not even that expensive because even the 15€/month/employee bil

by arlcode 24d ago

Open weights are certainly something that is very eagerly being adopted in some companies. It's not even that expensive because even the 15€/month/employee bill for people who use AI very little can stack up. Beside that though, many companies already have most if not all of their data in some cloud (Microsoft would be a prime example). Giving them a few extra bugs to get a (potentially) very useful tool is not out of the ordinary. If you are under the impression that not going AI would threaten your business right now (which may very well be true for some companies) then there isn't really a choice even if you believe the vendors will steal everything eventually (which they totally will)

protocolture 24d ago
>Open weights are certainly something that is very eagerly being adopted in some companies. A large local MSP that has significant colo space just started a big marketing push towards hosted LLMs for their corporate customers. I think its about to kick off everywhere.
- theshrike79 24d ago
  It's not just putting up colo space for local models. It's more about the harness and API proxy you use. They need to be smart enough to know when a (self)hosted model is enough and when to forward to a SOTA model. The SOTA model _can_ do everything, it's just expensive as fuck. But so is shoving a difficult task to a sub-par model that takes (relative) ages and comes back with the wrong result.
  - irthomasthomas 24d ago
    glm-5.3, kimi k3 and qwen3.8 are SOTA.
  - protocolture 23d ago
    I think the average corporation has 2 concerns largely: 1. Getting some exposure to LLMs while building out their AI strategy. 2. Preventing data loss via end users following desire paths to Gemini, OpenAI etc. You really don't need bleeding edge models for that. A lot of these things are going to be writing emails and adjusting config files and whatnot.

by arlcode 24d ago

protocolture 24d ago

>Open weights are certainly something that is very eagerly being adopted in some companies. A large local MSP that has significant colo space just started a big marketing push towards hosted LLMs for their corporate customers. I think its about to kick off everywhere.

theshrike79 24d ago
It's not just putting up colo space for local models. It's more about the harness and API proxy you use. They need to be smart enough to know when a (self)hosted model is enough and when to forward to a SOTA model. The SOTA model _can_ do everything, it's just expensive as fuck. But so is shoving a difficult task to a sub-par model that takes (relative) ages and comes back with the wrong result.
- irthomasthomas 24d ago
  glm-5.3, kimi k3 and qwen3.8 are SOTA.
- protocolture 23d ago
  I think the average corporation has 2 concerns largely: 1. Getting some exposure to LLMs while building out their AI strategy. 2. Preventing data loss via end users following desire paths to Gemini, OpenAI etc. You really don't need bleeding edge models for that. A lot of these things are going to be writing emails and adjusting config files and whatnot.