One of the strangest things in the AI industry is 'tokenomics'. It's not very clear why using GPT-4 in early 2023 was so expensive and then six months later 20 bucks could get you a fair amount of GPT-4 inference. This pattern has continued across various labs/providers for years--there is a continuous see-saw of pricing that doesn't seem related to anything.

So what open weight models do is at least provide a baseline of inference cost to add some sanity to the price markers. And of course predictability too--if you really want Kimi K2 instead of K3 you can still use it.

So the competitive pressure and predictability offered by open models is helpful for users

> The government should use procurement to create demand for portable, interoperable systems rather than permanent dependence on one API vendor.

Now, here is an idea that I have not heard before... and I think there is some merit to this. This is also the sort of thing that a state (looking at you CA, CO, IL, NY) could do, instead of just the federal government.

Is anyone using open weight models for agentic coding?

What is your stack and how much you pay per month?

How would you compare your experience to a typical subsidized plan like Claude Pro?

I’m asking because i keep hearing that open weight models are cheap and efficient - is that really the case in practice?

why would any software want to have Kubernetes moment? can't count how devop I know that is confused by it

Way over complicated for what most users need? Huh?

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