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You (currently) need a GPU to run any of the useful models. I haven't really seen a business use-case that runs it on the user's computer, but given the hardware requirements it wouldn't be very feasible to expect.

So you'll have to figure out how to run/scale the model inference. Cloud GPU instances are generally very expensive, and once you start needing to horizontally scale it'll get messy fast.

At least at the moment it's expensive, especially if it's either very light usage or very intensive usage - you either need just a few seconds of compute occasionally, or lots of compute all the time requiring scaling.

The "lucky" ones in this scenario are small-medium businesses that can use one or a few cards on-site for their traffic. Even then when you take the cost of an A100 + maintaining it, etc. OpenAI's offering still looks attractive.

I know there's a few services that try to provide an api similar to what openai has, and some software to self orchestrate it, I'm curious how those compare...



> once you start needing to horizontally scale it'll get messy fast.

It gets expensive fast, but not messy, these things scale horizontally really well. All the state is encapsulated in the request, no replication, synchronisation, user data to worry about. I'd rather have the job of horizontally scaling llama2 than a relational database.


For sure, and yeah it wouldn't be terrible you're right. You'd just need the api servers + a load balancer.

My thing is that dynamically doing that is still a lot compared to just calling a single endpoint and all of that is handled for you.

But for sure this is a very decent horizontal use-case.




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