- Lots of language semantics are unsupported in Octave (like Classes), and it’s purely a slow line by line interpreter so it’s very slow.

- Given the design / Cranelift IR translation here, RunMat can run natively on any compile target for which Cranelift [currently x86-64, aarch64 (ARM64), s390x (IBM Z), and riscv64], and targeting additional ISAs is easy. The net of this: you can write controls / logic in Matlab code and run it natively on device.

- GPU acceleration; the foundations are in place so RunMat can natively accelerate Tensor / Matrix math on GPUs, irrespective of device (eg CUDA / Metal / Vulcan / etc). Net of this is that you can do much bigger math calculations even faster (and without having to worry about moving things on/off GPU memory; there’s a configurable (and substitutable) planner built in that does scatter / gather intelligently for you). The AST is extensively typed, and we can support things like reverse-grade autograd by default -> your math runs even faster than would natively in Octave or even Matlab (I believe Matlab has a separate toolbox where you can do some of this, but it’s not natively how their matrix math works / they try and upsell for that).

- Once the package manager is complete, you can extend it. Octave doesn’t really have a package system per se.