Mojo 1.0 Beta

As someone in ML who's interested in performance, I'm keen for Mojo to succeed - especially the prospect of mixing GPU and CPU code in the same language. But I do wonder if the changes they're making will dissuade Python devs. The last time I booted it up, I tried to do some basic string manipulation just to test stuff out, but spent an hour puzzling out why `var x = 'hello'; print(x[3])` didn't work, and neither did `len(x)` (turns out they'd opted for more specific byte-vs-codepoint representations, but the docs contradicted the actual implementation).

Hopefully they get Mojo to a good place for more general ML, but at the moment it still feels quite limited - they've actually deprecated some of the nice builtins they had for Tensors etc... For now I'll stick with JAX and check in periodically, fingers crossed.

When I first heard about Mojo I somehow got the impression that they intended to make it compatible with existing Python code. But it seems like they are very far away from that for the foreseeable future. I guess you can call back and forth between Python and Mojo but Mojo itself can't run existing Python code.

Sadly for them, Nvidia didn't stay still in the meantime and created the next generation of CUDA, CuTile for Python and soon for C++, through CUDA Tile IR (using a similar compiler stack based on MLIR).

Event though it's not portable, it will likely have far greater usage than Mojo just by being heavely promoted by Nvidia, integrated in dev tools and working alongside existing CUDA code.

Tile IR was more likely a response to the threat of Triton rather than Mojo, at least from the pov of how easy is to write a decently performing LLM kernel.

Advertising prominently with "AI native" seems necessary today, at least for some folks. To me, that's kind of off-putting, since it doesn't really say anything.

Can anyone of the AI enthusiasts here explain, why, or, what is meant by

> As a compiled, statically-typed language, it's also ideal for agentic programming.

Is there any project that showcases Mojo for running neural network models on the GPU - like ideally something like llama.cpp that could run one or more existing models to showcase the readability and performance?

I’m relatively new to programming but I wish they had used a functional language syntax rather than an object oriented one as the basis for mojo.

From my experience, AI revolves a lot around building up function pipelines, computing their derivatives, and passing tons of data through them; which composability and higher order functions from functional programming make it a breeze to describe.

I also feel that other fields than AI are moving towards building up large functional pipelines to produce outputs, which would make mojo suitable for those fields as well. I’m building in the space of CAD for example and I’d love to use a “functional mojo” language.

Julia is more mature for the same purposes, and since last year NVidia is having feature parity between Python and C++ tooling on CUDA.

Python cuTile JIT compiler allows writing CUDA kernels in straight Python.

AMD and Intel are following up with similar approaches.

If Mojo will still arrive on time to gain wider adoption remains to be seen.

I was excited when Mojo launched and thought it might grow big quick. I don't see much traction. The pitch is compelling. What could be the issue?

I remember reading about this 4 years ago as the new Chris Lattner project and was super excited, though a little skeptical.

I think that nowadays with vibe/agentic coding, high performance Python-like languages become ever more important. Directly using AI agents to code, say, C++, is painful as the verbose nature of the language often causes the context window to explode.

Right now majority of beginners start programming with a high-level language, say Python or JavaScript - then for more advanced system-level tasks pickup C/C++/Rust/Zig etc.

If Mojo succeeds, it could be the one language spanning across those levels, while simplifying heterogeneous hardware programming.

I do wonder if Mojo was a great idea just a little too late to the party. Porting ‘prototypes’ from Python to lower level languages is fairly trivial now with LLMs.

Doesn't anyone here have _one_ kind word to say about its features? Every one seems to be starting with "on the other hand".

> We have committed to open-sourcing Mojo in Fall 2026.

https://docs.modular.com/mojo/faq/#will-mojo-be-open-sourced

Am I old or remembering this wrong... didn't Zuck write the first iteration of Facebook in PHP, and then spend millions to hire people to write something that converted the code to C++?

Very bold of them expecting people to use a language with a closed source compiler in the 2020s.

I am actually on a lookout for a low level language which compiles to web assembly to write a (relatively small) supervised learning model which I plan to be good enough for 5 year old phone CPUs. I have a working prototype in Julia and was planning on (eventually) rewrite it in Rust mostly for the web assembly target. I come from a high level language background so the thought of rewriting in rust is a little daunting. So I was excited to learn about Mojo and find out if they had a WebAssembly target in their compiler.

But then I read this:

> AI native

> Mojo is built from the ground up to deliver the best performance on the diverse hardware that powers modern AI systems. As a compiled, statically-typed language, it's also ideal for agentic programming.

Well, no thank you. I know the irony here but I want nothing to do with a language made for robots.

>No more choosing between productivity and performance - Mojo gives you both.

That's a very big claim.

Does it have the indentation thing? That would be a no go for a lot of people