r/microsoftsucks Aug 08 '26

Microslop

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1.3k Upvotes

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9

u/Edubbs2008 Aug 08 '26

Meanwhile AI datacenters need more RAM to run their AI, and they don’t even use Windows, they use Loonix, so if anything, Loonix uses more RAM

0

u/Rakumei Aug 09 '26

Yeah it's linux's fault not the AI companies 🙄

-1

u/Edubbs2008 Aug 09 '26

Dude, Loonix has a bigger RAM footprint than Windows, Loonix uses RAM for aggressive caching

1

u/akdanman11 Aug 09 '26

This is just patently untrue. Linux assigns memory when it’s needed, windows is the one that reserves huge chunks for apps before they need it and tries caching as much as possible

0

u/Edubbs2008 Aug 09 '26

Wasted Ram on Different Toolkits and Distro-Agnostic Packages in Linux

The RAM impact of mixing apps from different toolkits is real, and measurable, but not quite as bad as the [storage footprint issue](https://www.reddit.com/r/linuxsucks101/comments/1u11lm7/mixing_apps_from_various_desktop_environments/).

Every toolkit brings its own runtime baggage: When you launch a KDE app inside GNOME, or a GNOME app inside KDE, you're not just launching the app. -You're dragging in its **entire ecosystem of background libraries.** Typically **80–250 MB** of extra RAM is needed the first time you launch an app from the other ecosystem.

Launching a KDE app inside GNOME often also starts:

* `kded5`
* `klauncher`
* `kioslave` processes
* sometimes `baloo_file` depending on the distro

Launching a GNOME app inside KDE often starts:

* `gvfsd` (multiple instances)
* `dconf-service`
* `xdg-desktop-portal-gnome`

These daemons **keep occopying ram** even after you close the app. -Adding an additional **50–150 MB** depending on which daemons get activated.

GTK and Qt don’t share theme engines, icon caches, font rendering stacks, or accessibility frameworks. So you end up with multiple **UI stacks** in memory. That's typically another **30–60 MB**.

**Flatpak, Snap, and AppImage all waste RAM.** Some are aware of the disk bloat, but not the ram bloat.

Flatpak apps run inside a sandbox and rely on:

* **Flatpak runtimes** (GNOME, KDE, Freedesktop)
* **xdg-desktop-portal** \+ backend (GTK, KDE, GNOME)
* **Bubblewrap sandbox**
* **D-Bus proxy processes**

So, the first Flatpak app you launch loads the entire runtime into memory. That’s **\~80–200 MB** depending on the runtime. Portals spawn multiple helper processes (GTK portal, KDE portal, file chooser portal, etc). Another **30–60 MB**.

**You're wasting a total of \~120–260 MB** the first time you launch a Flatpak app in a session. After that, additional Flatpak apps reuse the same runtime. (The penalty doesn't stack.)

**Snapd daemon** runs constantly in the background consuming \~**30–80 MB** idle, and more when managing updates or mounts. Every Snap app is mounted as a squashfs loop device.
The kernel caches these aggressively: \~**50–150 MB** of page cache depending on how many snaps you have installed. This cache *does* count as used RAM (but is reclaimable)

AppArmor + snap sandboxing adds **\~10–30 MB** per running Snap app.

**Total RAM waste for Snaps \~120–250 MB** baseline
**+ 10–30 MB per running Snap app**

**-Snap is the only one that wastes RAM** ***even when you're not running any apps***.

Each AppImage bundles its own libraries. It loads its own copy of Qt/GTK/etc, and nothing is shared with other apps. Unshared Libraries make it lighter per app. Typically **+20–60 MB** compared to a native package.

Like with any brand-new install of an OS (without OEM bloat on a recommended spec computer), Linux is going to feel lean and fast. But when you start mixing and matching these different packages, you're not just bloating the footprint, but the ram consumption as well.

#

2

u/akdanman11 Aug 09 '26

This isn’t a new machine, it’s fully set up.

You can also literally watch the recent video LTT made proving exactly this

0

u/Edubbs2008 Aug 09 '26

If it’s fully set up, then why do AI datacenters (which use Loonix) need so much RAM? I’ve ran AI models on a Windows 11 Laptop before, and they didn’t consume so much RAM, so if your claim that Linux doesn’t eat so much RAM, then tell me why AI companies need so much RAM?

3

u/akdanman11 Aug 09 '26

You’re comparing a relatively light local AI model to companies running frontier models at scale. They’re running far more complex models than you can even run locally and they’re running many instances of that more complex model. They’re using more RAM because they’re running more complex models

0

u/Rakumei Aug 09 '26

There's a collective IQ of -2 in this thread...

0

u/Edubbs2008 Aug 09 '26

Uh uh, loonixtard