Having written a lot of Mojo over the last two year, just for fun, it's a really cool language. Ownership model adjacent to Rust, comptime in the realm of Zig, rich type system, first class SIMD support, etc. Performance wise it's the first language in long time that isn't just an LLVM wrapper. LLVM is still involved, but they are using it differently than say, Rust or Zig.

Very excited for Mojo once it's open sourced later this year.

I felt the same way, even after browsing around on the website, and somehow I got to https://mojolang.org/docs/manual/quickstart/, which brings you to mojolang.org instead, which is the real website of the language it seems, instead of "Modular" which I guess is the business.

https://mojolang.org is a lot better as a introduction to the language for a programmer, at least for me, compared to whatever I could find on the modular.com website.

It's supposed to be (currently) a fully native, Python-like language, but for GPUs primarily. Though I am seeing it as having a future as a fully native Python alternative that might get interesting.

I hope with 1.0 (havent fully read the article yet) they stop breaking language features / syntax because they did quite a few different changes over time, their overall goal is to be a fully native superset of Python.

I do see this one overtaking Nim over time, which kind of saddens me, because I like Nim for what it is, but Mojo trying to be a superset of Python is a no-brainer for most Python developers. Reminds me of how a lot of Go devs were former Python devs not C++.

Python, but good.

The point is that Mojo compiles to MLIR for programming on heterogenous compute and GPU so something like Pydantic isn't really comparable here.

The alternatives would be stuff like CUDA

> Finally, we will continue to progressively open-source more of the Mojo language, as well as components in MAX that we have built with it. Our commitment remains unchanged – we will open source the Mojo compiler and toolchain in 2026.

The value has already been materialized. They were acquired by Qualcomm for $3.9 billion.

C and C++ were closed source for quite some time, they still are in places like commercial embedded OSes and console dev kits, even when they happen to be GCC and clang forks nowadays.

Clang actually has replaced most GCC forks exactly because vendors can keep the fork closed source.

Their website has a banner suggesting news about open sourcing of the compiler at some Aug 18 convention.

I know right? Would be better to have a banner with the language logo than some totally out of place aislop image, almost makes you think this is a random person's blog and not the official Mojo site

I spotted the exact same thing with the AI image. makes the whole thing immediately feel cheap, it's wild

"Normal" keeps getting more and more depressing.

Did they think that image would make them look fun or interesting? Because it's exactly the opposite.

> I guess that's the new normal.

Yes, so basing confidence on it is totally bogus. Such comments are cheap and add nothing to the discussion of Mojo reaching 1.0 status.

Isn't Mojo expressly for building AI frameworks? It isn't really needed or special as a language by-itself. It's main purpose is to make it easier to program these high end graphics cards for AI.

So maybe an AI image isn't the worst.

It's probably very messy and not a great baseline for outside contributors to start create PRs.

That's the favorable interpretation, atleast.

> They should show some performance comparisions between PyTorch and Mojo, PyTorch+kernel compilation + Triton vs Mojo, ThunderKittens vs Mojo.

The fact that they release 1.0 without doing this, I think says a lot. I personally haven't even started looking into Mojo because of the closed source stuff, but usually you can tell what's going on by looking for what's obviously missing.

Aren’t they already separated? Max is an inference runtime, written in Mojolang, which uses the MLIR compiler chain to target diverse accelerator hardware.

The premise of Mojo used to be that it was a superset of Python so in theory LLMs would benefit from that but I'm not sure how much divergence there's been

Are there any benchmarks on which languages models perform best?

You may have heard of it already, but Nim has existed in this space for some time.

like finding a rock of gold underground and tossing it away because it’s dirty?

Pointless? If compiled mojo is faster, more memory-safe, and more hardware independent, that doesn’t seem pointless at all to me.

(And now in the age of LLMs, the barriers to get started with a new programming language are lower than ever)

Do you know CUDA or Triton? The point of Mojo was to replace GPU kernel programming langs with a Pythonic one that was more familiar

Sounds like you're just lazy. Which is fine. You'll probably have a okay career. But not a great one.

this language predates the rise of "AI" (you probably mean harnessed LLMs, but I'll forgive you) by several years. This is the 1.0 release.