The hardware requirements aren't evolving and the local models have only been improving.

It's not like you'd lose capabilities, if anything this solution just gets better with time.

If the newer models require more/better hardware then you’ll lose capabilities.

I think you’re better off renting GPU instances and running all the software on those. It’ll be cheaper than Anthropic and OpenRouter but slightly more expensive than electricity and depreciation of hardware.

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cogman10 4 hours ago | parent [-]

The newer models don't require more/better hardware. There's a small army of local llm enthusiasts who are running LLMs using 3090s and H100s because they have lots of memory. Them being old isn't really that big of an issue as the compute power needed is relatively low all things considered.

The number of parameters needed for these open weight models has mostly stabilized so the actual memory requirements aren't likely to change all that much.

	▲	dannyw 2 hours ago \| parent [-]
		Correct. The main bottleneck with LLM inference is, and have always been, memory bandwidth. TPS = active weights in GB / your memory bandwidth. That’s it for decode. That’s all.