Of typical homelabs that are posted and discussed.

The online activity of the homelab community leans towards those who treat it as an enjoyable hobby as opposed to a pragmatic solution.

I'm on the other side of the spectrum. Devops is (at best) a neutral activity; I personally do it because I strongly dislike companies being able to do a rug-pull. I don't think you'll see setups like mine too often, as there isn't anything to brag about or to show off.

It still seems to have the same pitfalls as all the other image generation models. I ran it through my test prompt (wary of posting it here, lest it gets trained on) - it still cannot generate something along the lines of "object A, but with feature X from Y", where that combo has never been seen in the training data. I wonder how the "astronaut riding unicorn on the moon" was solved...

EDIT: after significant prompting, it actually solved it. I think it's the first one to do so in my testing.

It's a shame that it's not on OpenRouter. I hate platform lock-in, but the top-tier "deep think" models have been increasingly requiring the use of their own platform.

Sweet! I love clever information theory things like that.

It goes the other way too. Given that LLMs are just lossless compression machines, I do sometimes wonder how much better they are at compressing plain text compared to zstd or similar. Should be easy to calculate...

EDIT: lossless when they're used as the probability estimator and paired with something like an arithmetic coder.

I just ran this with Gemini 3 Pro, Opus 4.6, and Grok 4 (the models I personally find the smartest for my work). All three answered correctly.