Linux libraries sometimes can’t even install on a newer kernel.

i’m curious where you run into this. i’ve never had this issue in 10 years of using Linux, most of which being on Arch with the latest kernel

in a container

well there’s your issue. i get not liking the OS, but actively crippling your project will cripple your project.

containers on macOS do kinda suck

just a silly turn of phrase meaning: you should know that this is what you signed up for

so, it’s the same.

saying “Linux does dynamic linking and Window does static linking” is both false and a mischaracterization. Windows absolutely does dynamic linking with its Dynamically Linked Libraries (.dll). how dependencies are linked is up to the developer and whatever hardware constraints. one reason i like Rust is that it prefers static linking, and a lot of tool chains are moving in that direction. the reason Linux distros push people toward their internal package management tools (eg apt) is to have tighter control over dynamic linking.

and we’re also glossing over scoop and chocolatey and winget and Docker.

but that’s where you get to stuff like flatpack and snap and Nix that try to contain the dynamic dependencies.

i don’t think downloading exes hoping that Windows has stuffed enough DLLs into the OS and just running them is a better solution.

super fair. i am a Linux guy normally. i’m just being honest. i wish there was a better more open alternative.

if you want to go with the Linux alternative it’s going to cost. get at least 32GB of RAM and at least a 4090 to run the kind of models you’re asking for. it’s the way she goes

it’s Ubuntu dawg. you get what you pay for.

honestly it’s hard to beat Macs these days in this space for two reasons:

• unified memory means that you don’t have to load up on RAM just to load the model and then also shell out for a video card with barely enough VRAM to fit a basic language model
• their supply chain is solid and has mostly avoided the constraints that other OEMs and parts manufacturers are struggling with

pricing is tough. sure, crypto is on its way out, but GPUs are still the platform of choice for most neural net workloads (outside of SoCs like Apple M-series). i built a PC in late 2024, and it’s easily worth twice what i paid for it.

i guess it would be nice, but packages being a few months out of date is pretty normal for Ubuntu, in my experience. i’m not sure what their testing process is like, but part of using something like Ubuntu is stability guarantees. if they felt like the couldn’t do that for newer versions for whatever reason (resource constraints, lack of downstream interest from stakeholders, etc) they’re not necessarily obligated to.

there’s a world of options. this is an LTS distro. use Arch or Nix or whatever if you want the latest packages. i actually switched to NixOS because the CUDA drivers were too new on Arch, and i wanted a better way to pin versions.

or i dunno keep publicly complaining about it until someone does the work for you

i’ve been looking for a silver bullet in this space. hurl[1] seems promising as well. i feel like Bruno has always been jank, and going 1.0 didn’t help. at work i’ve stuck to vibe coding my API test code with a stack of TOML configs, that way i get to reuse/test my client code as well.

what i want is something version controllable with lightweight dependencies that i can automate easily. i’m afraid that discounts this project. not going to ask my team to download Yet Another Electron API client UI. i’m hesitant to introduce hurl, which can at least be scripted.

1: https://hurl.dev/

i’d vibe code something in Python for this tbh, but i have some expertise in this area already. you could even get some classification going with a YOLO model to help you narrow down the search. it won’t have a GUI unless you count Jupyter notebooks.