Love this intentionality: ” Our open source approach has been deliberate: we’ve found that small and tight-knit design teams (not committees) are the best for finding the “soul” of a language, but that feedback from a broader community is essential to escape an echo chamber. As such, we first open-sourced the Mojo standard library, then released hundreds of thousands of lines of kernel code written in Mojo, tools, and support. We built together with community feedback and public design proposals, and are now open sourcing the compiler. We will continue to open our processes further as Mojo keeps maturing.”
eatonphil
I did a review of Mojo a few months ago focused on Python compatibility if anyone's curious about that angle. Admittedly it is a narrow angle. I want to take another look at Mojo sometime not focused on Python.
One of my favourite features of Mojo is linear types and how deeply they have been integrated into manual memory management - see:https://x.com/melodyogonna/status/2085089269484343725?s=20.
When I first learned about linear types, my first thought of the use case was making manual allocations and deallocations safer without sacrificing usability, but I didn't know what that could look like; now I do. This is great because in Mojo, pointers are surfaced a lot more than in, say, Rust, but such sharp tooling in a language you expect to be safe by default can be problematic. Linear types, combined with the origin system, give the language a lot of flexibility; it is like using a sharp tool with a safety glove: the tool isn't any less sharp, but the chances of accidentally injuring yourself are reduced.
So I think the permissive license like Apache 2 without opening up for upstream contributions would be the way of future open source development. In a very similar way of SQLite. It definitely will help shield off a bunch of AI generated contributions first and foremost and then, aligning mental model with the human contributions with Mojo leader team.
SwellJoe
As long as it was proprietary, I could ignore it. Now, I guess I have to learn a little something about it.
embedding-shape
Finally, gonna be a lot of fun to finally play around with, lets see how it compares to Python for ML ultimately :) The build process is quite heavy, pinning all my cores at 100% on a Threadripper 9970X for ~15 minutes which isn't so common.
Curious to know what setups they've tested Mojo on so far, as I understood it to be mainly for ML/AI stuff, so commonly pretty beefy workstation, yet I'm getting warnings that it's not recognizing my GPU (RTX Pro 6000). Seems easy enough to work around by editing the gpu_mapping in MODULE.bazel so I guess isn't a huge issue. Just strange to see a really CPU-heavy build, then not recognizing a somewhat common "prosumer" GPU (common in the ecosystem and expected user audience at least).
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totalperspectiv
This is really exciting. I've been using Mojo off and on for side projects over the last two years.
(copying from some previous Mojo threads) It's got an ownership system adjacent to Rust, comptime similar to Zig, and a first class dependent type system. Even more exciting, is that uses LLVM (to the best of my understanding) in some novel ways and for more optimizations.
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setopt
Very exciting. Closed source was one of the main things making me not try it out yet.
Any good resources for getting started? And anything on doing NumPy/SciPy-like stuff in it?
Technically soruce available now with the promise of accepting contributions (thus becoming fully open source) early next year. But since it is an Apache 2 license (like the rest of the LLVM project) you are already allowed to fork and contribute to your own fork right now, just no upstreaming.
For many the closed source nature of the compiler was a knock-out criterion. We will see if Mojo can gain traction now or if it has missed its window of opportunity.
I found it a bit curious that Mojo seems more readable, while at the same time less compact, than Rust.
At least according to my small experiment:
https://x.com/smllmp/status/2055602226240893043
Love this intentionality: ” Our open source approach has been deliberate: we’ve found that small and tight-knit design teams (not committees) are the best for finding the “soul” of a language, but that feedback from a broader community is essential to escape an echo chamber. As such, we first open-sourced the Mojo standard library, then released hundreds of thousands of lines of kernel code written in Mojo, tools, and support. We built together with community feedback and public design proposals, and are now open sourcing the compiler. We will continue to open our processes further as Mojo keeps maturing.”
I did a review of Mojo a few months ago focused on Python compatibility if anyone's curious about that angle. Admittedly it is a narrow angle. I want to take another look at Mojo sometime not focused on Python.
https://theconsensus.dev/p/2026/03/12/mojos-not-yet-python.h...
One of my favourite features of Mojo is linear types and how deeply they have been integrated into manual memory management - see:https://x.com/melodyogonna/status/2085089269484343725?s=20. When I first learned about linear types, my first thought of the use case was making manual allocations and deallocations safer without sacrificing usability, but I didn't know what that could look like; now I do. This is great because in Mojo, pointers are surfaced a lot more than in, say, Rust, but such sharp tooling in a language you expect to be safe by default can be problematic. Linear types, combined with the origin system, give the language a lot of flexibility; it is like using a sharp tool with a safety glove: the tool isn't any less sharp, but the chances of accidentally injuring yourself are reduced.
Recent and related:
Mojo 1.0 - https://news.ycombinator.com/item?id=49261128 - Aug 2026 (244 comments)
Is this a case of of Qualcomm commoditizing their complements? Does Mojo have a potential for disrupting Nvidia's current market position?
https://www.joelonsoftware.com/2002/06/12/strategy-letter-v/
So I think the permissive license like Apache 2 without opening up for upstream contributions would be the way of future open source development. In a very similar way of SQLite. It definitely will help shield off a bunch of AI generated contributions first and foremost and then, aligning mental model with the human contributions with Mojo leader team.
As long as it was proprietary, I could ignore it. Now, I guess I have to learn a little something about it.
Finally, gonna be a lot of fun to finally play around with, lets see how it compares to Python for ML ultimately :) The build process is quite heavy, pinning all my cores at 100% on a Threadripper 9970X for ~15 minutes which isn't so common.
Curious to know what setups they've tested Mojo on so far, as I understood it to be mainly for ML/AI stuff, so commonly pretty beefy workstation, yet I'm getting warnings that it's not recognizing my GPU (RTX Pro 6000). Seems easy enough to work around by editing the gpu_mapping in MODULE.bazel so I guess isn't a huge issue. Just strange to see a really CPU-heavy build, then not recognizing a somewhat common "prosumer" GPU (common in the ecosystem and expected user audience at least).
This is really exciting. I've been using Mojo off and on for side projects over the last two years.
(copying from some previous Mojo threads) It's got an ownership system adjacent to Rust, comptime similar to Zig, and a first class dependent type system. Even more exciting, is that uses LLVM (to the best of my understanding) in some novel ways and for more optimizations.
Very exciting. Closed source was one of the main things making me not try it out yet.
Any good resources for getting started? And anything on doing NumPy/SciPy-like stuff in it?
PR here: https://github.com/modular/modular/pull/6904
"Qualcomm to Acquire Modular 06/24/2026"
https://investor.qualcomm.com/news-events/press-releases/new...
Can acqui-death be far away...?
Such an exciting time for Mojo, I don't think people realize just yet the innovation being brought to fore here.
Related:
Mojo 1.0
https://news.ycombinator.com/item?id=49261128
What a beautiful standard library btw. Much to learn and take from.
"Modular Confidential (obviously), May 14, 2022"
lol, feels like espionage
https://github.com/modular/modular/blob/main/KGEN/docs/Desig...
Compiler walkthrough
https://github.com/modular/modular/blob/main/KGEN/docs/MojoC...
Related post with relevant pr: https://news.ycombinator.com/item?id=49347777
Technically soruce available now with the promise of accepting contributions (thus becoming fully open source) early next year. But since it is an Apache 2 license (like the rest of the LLVM project) you are already allowed to fork and contribute to your own fork right now, just no upstreaming.
For many the closed source nature of the compiler was a knock-out criterion. We will see if Mojo can gain traction now or if it has missed its window of opportunity.