Short answer: there is none. You can't get frontier-level performance from any open source model, much less one that would work on an M3 Pro.

If you had more like 200GB ram you might be able to run something like MiniMax M2.1 to get last-gen performance at something resembling usable speed - but it's still a far cry from codex on high.

at the moment, I think the best you can do is qwen3-coder:30b -- it works, and it's nice to get some fully-local llm coding up and running, but you'll quickly realize that you've long tasted the sweet forbidden nectar that is hosted llms. unfortunately.

A local model with 18GB of ram that has the same quality has codex high? Yeah, nah mate.

The best could be GLN 4.7 Flash, and I doubt it's close to what you want.

"run" as in run locally? There's not much you can do with that little RAM.

If remote models are ok you could have a look at MiniMax M2.1 (minimax.io) or GLM from z.ai or Qwen3 Coder. You should be able to use all of these with your local openai app.

Nothing. This summer I set up a dual 16GB GPU / 64GB RAM system and nothing I could run was even remotely close. Big models that didn't fit on 32gb VRAM had marginally better results but were at least of magnitude slower than what you'd pay for and still much worse in quality.

I gave one of the GPUs to my kid to play games on.

Z.ai has glm-4.7. Its almost as good for about $8/mo.

+1 to "it's a stupid benchmark".

It shows that these are nowhere near anything resembling human intelligence. You wouldn't have to optimize for anything if it would be a general intelligence of sorts.

Why stupid? Vector images are widely used and extremely useful directly and to render raster images at different scales. It’s also highly connected with spacial and geometric reasoning and precision, which would open up a whole new class of problems these models could tackle. Sure, it’s secondary to raster image analysis and generation, but curious why it would be stupid to persue?

It could still be special-case RLHF trained, just not up to perfection.