Sorry, but what are you talking about? This is a 120B-A6B model, which isn't runnable on any laptop except the most beefed up Macbooks, and then will certainly drain its battery and cook your legs.

You can easily run a quant of this on a DGX Spark though. Seems like a small investment if it meaningful improves Lean productivity.

Is it though?

Most people I know that use agents for building software and tried to switch to local development, every single time they switch back to Claude/codex.

It's just not worth it. The models are that much better and continue to get released / improve.

And it's much cheaper unless you're doing like 24/7 stuff.

Even on the $200/m plan, that's cheaper than buying a $3k dgx or $5k m4 max with enough ram.

Not to mention you can no longer use your laptop as a laptop as the power draw drains it - you'd need to host separately and connect

A single DGX Spark can service a whole department of mathematicians (or programmers), and you can cluster up to 4 of them them to fit very large models like GLM-5 and quants of Kimi K2.5. This is nearing frontier-level model size.

I understand the value proposition of the frontier cloud models, but we're not as far off from self-hosting as you think, and it's becoming more viable for domain-specific models.

That's great news- I wonder if that will help drive cloud costs down too