Steam takes care of the distribution and version mumbo jumbo for you with their runtime

https://github.com/ValveSoftware/steam-runtime

https://gitlab.steamos.cloud/steamrt/steam-runtime-tools/-/b...

Nobody's running SDXL on an 80W GPU when they're talking about generating images, and you also have to take into account training and developing SDXL or the relevant model. AI companies are spending a lot of resources on training, trying various experiments, and lately they've become a lot more secretive when it comes to reporting climate impact or even any details about their models (how big is ChatGPT's image generation model compared to SDXL? how many image models do they even have?)

It promotes an open research environment where external researchers have the opportunity to learn, improve and build. And it keeps the big companies in check, they can't become monopolies or duopolies and increase API prices (as is usually the playbook) if you can get the same quality responses from a smaller provider on OpenRouter

I tried, but they basically said we can't help anymore in this matter and disconnected me and I saw no further way to escalate. This was in the US. In the EU when I had another problem with Amazon and CS was unhelpful I was able to escalate via relevant authorities and it eventually got someone from Executive Customer Relations to send an actual human-written email apologizing for the whole ordeal and resolving my situation

Yep those are exactly the same considerations. LLM providers will have inconsistent latency and throughput due to batching across many users, while training with cloud GPU servers can have inconsistent bandwidth and delay for uploading mass training data. LLM providers are always limited in how you can use them (often no LoRAs, finetuned models, prompt restrictions)