Best AI coding models

`2:29:23`

What's amazing to me is that you could rattle off so many different contenders. That this market is so wide open, that it does actually change back and forth, that we have real competition, that there are so many labs that are able to get either to the frontier or close to it. That, by the way, is remarkable. I still don't fully understand that. But to answer your question, the best model in general right now is Fable. The second-best model, in my opinion, is Opus 5. But the tier just below Opus 5, and it's not even that they're always below, sometimes they're ahead. I'll get to that in a second. I would rank GPT Sol very good. Grok 4.6 I just started testing a few days ago. I had this wonderful test that I've set up by accident where I translated this Python library into Rust. Uh, the screensaver you just saw with all the cool animation? That's powered by a Python library called Terminal Text Effects. Really cool library. We've been using it since the first day of Omarchy. The problem with that is it's written in Python, so when it starts up, especially on a laptop, and it runs in Python, it uses all of your CPU to do these effects, and therefore, it means it uses about 30 watts of energy, and it spins up your fans, and it drains your battery. Doesn't really matter on a local computer, but it does matter on a laptop. So I thought, "Do you know what?

This sounds like a problem for Rust." So first I gave Fable the challenge, and all I told it was, "Here's the source code for the Python library," this TTE library that had a bunch of dependencies and so forth. "I want a Rust version of this with no dependencies, a single executable." Like, that's what Rust does. So basically, I want it in Rust. I want it to be pixel perfect, frame by frame, do a full analysis, don't stop until you're finished.

`2:31:29`

I kid you not, in just under 45 minutes, it was like Am I heard all? I'm finished. I've checked everything. I have reduced the startup time from 86 milliseconds to two milliseconds. I have sped up the execution time by 9.6 times, I believe it was. The executable is three megabytes. Do you wanna run it?

`2:32:02`

... and I don't know why I'm surprised, because this translation job is something we've known for a while that AI is pretty good at, but it was still staggering to me that I could one-shot a full translation of a Python library I had been using for a year, that others had been using for much longer, and turn it into a Rust executable without knowing any Rust, without looking at the Rust code at all, and produce this executable that I then told the agent right after, "This is great. Ship it." It packaged it up as a new package. It told me, "What do you want it to call?" "Uh, let's call it TTFX. Let's create a new Git repo." It sets up the Git repo. "Let's create a new package, build package for our build system." It puts that up. "Let's push it out. Let's open the pull request to the Omarchy itself so we switch around from TTE, the Python implementation, to TTFX." It does all of it, and I'm just sitting there. And again, I'm already at this point fully delirious with agent acceleration, and I still had to lean back and I go like, "This is AGI, isn't it? This is what AGI looks like. If we have... If these moments are just what it is all the time, this is AGI."

`2:33:21`