> The number of people with hardware to run a model like that is very small.

That's not the problem anyone is facing, and analysis anyone is doing. At all.

The problem is the huge AI-related budget that companies who dove head first onto AI are facing.

Therefore the problem everyone is faced with boils down to whether they keep paying the likes of OpenAI a de-facto business tax, or they replace that tax with a one-off CapEx invoice followed by a utilities bill.

And you don't need a frontier model to do most things. In fact, the biggest challenge in using local models in agentic coding is the models supporting these agent-based tools.

> It's going to be many years before hardware to run medium size local models is widely available.

Nonsense. Speaking for myself, my employer already introduced a hard cap on AI credits while rolling out hardware support for local models, and even went to the extents of rolling out workstations with 64GB of RAM as a baseline. Consequently, we are using the likes of gemma4 for a fair share of everyday tasks. This has a transformative effect on your workflows because suddenly you don't ration tokens, and agent orchestration doesn't become a cash guzzler. So far the only constraints are tool support and token throughput, but that's not a concern.