> LLMs in 2022 were very impressive.

No they weren't. They were a gimmick - it is only in the past 6 or so months that frontier models have started to do stuff beyond mere gimmicks when it comes to coding, and you could make the argument that Mythos has been the first 'Holy shit' moment that we've had that has stepped us beyond 'Yeah that's really neat but...'

> Those models are absolutely runnable on consumer hardware now,

A sub 50B model is awful and can't even write proper English sentences half the time, to say nothing of how bad its world knowledge is. Try the 32B Gemma 4 local model for a week and then go back to Claude and then get back to me.

> We're long past "danger". If what we have is the best we'll ever have open source, we're already in an excellent position.

Not sure what to tell you other than that you and I have very different standards. What we have locally right now is barely more than a glorified autocomplete, and it feels worse than using ChatGPT 2 years ago because the context window is less and it doesn't have good webhooks on consumer setups. Another thing I'd say is that you clearly have no clue what 'consumer hardware' means, or what consumers that can even get this stuff running locally would have to do to get it to even rival the frontier models in terms of their usability (most consumers are't going to just boot into Ubuntu and run this thing from a command line) flow, to say nothing of the hardware requirements. I'd love to never use Claude or Gemini or ChatGPT again for both privacy and money reasons, but the quality of outputs and depth of thinking and writing ability between even the very best local models you can run right now is many orders of magnitude less than what you get using distributed frontier models, and those 'very best' local models require a top of the line machine that 99.9999% of consumers don't have and would never consider buying. The cloud models all have like a trillion(!) parameters now. It isn't even close.

I sure hope the local side of things massively improves over the next 2-3 years, but based on how this has gone my guess is that in 3 years you'll be lucky, if you have very top of the line hardware, to get benchmark performance that we had 6 months ago with the frontier models. The distributed hardware/memory gap is just too big.

> No they weren't. They were a gimmick - it is only in the past 6 or so months that frontier models have started to do stuff beyond mere gimmicks when it comes to coding

This is simply untrue. Using agentic orchestration I was writing production code daily 3 years ago. Hallucinations happened sometimes and context window was smaller (so you had to do some funky workarounds to deal with larger codebases), but it was workable. There have been a lot of marked improvements from a code perspective then - a lot model related yes, but also a lot in the ease of use, interfaces, etc.

> Another thing I'd say is that you clearly have no clue what 'consumer hardware' means, or what consumers that can even get this stuff running locally would have to do to get it to even rival the frontier models in terms of their usability (most consumers are't going to just boot into Ubuntu and run this thing from a command line) flow, to say nothing of the hardware requirements.

You've moved the goalposts. My point was that the "danger" of no new open models being released isn't that high as the existing ones are already impressive. Their ease of use or daily driving isn't relevant to that. If there were a need, someone could wrap a clean interface and support around it, or run it as their own cloud solution.

You seem to be arguing something adjacent to my point, which is fine I guess but I have little to say. Also multiple of your comments have come across quite aggressive and rude. Just food for thought if you want to work on that or not.