Title says most of it. Super easy install only hang is the broadcom driver that I got by Bluetooth tether to my iphone.

Everything works and kind of looks like MacOS with Plank installed and some tweaks.

Really amazed at how fast and capable this $80 little old lappy is. Bloody GREAT keyboard too. All the Mac function keys work as well for Audio, Screen and KB brightness etc. I even swapped the CTRL and Command keys so my Mac muscle memory for cut and paste and such still works.

Fan almost never runs and if it does it is super slow... just doesn't get hot like it used to.

Just wanted to turn some others onto this find.

I am very excited about the future of local AI. With the spread of AI agents, the amount of VRAM now achievable locally, the quality of small and medium LLMs, and the community growing around all of this, the future is looking very good.

I am writing this to document my successes with the following:

• Mac Pro 2019
• Ubuntu 24.04.4 LTS (Ubuntu Server specifically, in my case)
• Dual AMD Radeon PRO W6900X with Infinity Fabric Link Bridge
• Dual AMD Radeon PRO W6800X Duo with Infinity Fabric Link Bridge
• ROCm 7.2.3
• PyTorch 2.10
• Triton 3.6
• vLLM (Write up pending)
• Hermes Agent (Research Pending)

I wrote a couple of old guides. Check them out for reference, as needed:

• Linux & Local LLM/AI (Useful for moving from macOS the first time)
• Proxmox, Ubuntu, ROCm, & Local LLM/AI (Useful for Proxmox setup)

I'm going to focus on setting up Ubuntu and all the packages needed for the infrastructure of local AI.

Important: This is an experimental community guide. Some parts involve patched kernels, unsupported GPU configurations, and boot-level PCIe changes. This worked for my Mac Pro 2019 systems, but you should expect troubleshooting, and you should be comfortable recovering from a failed boot. I am not responsible for any outcome of using this guide, whether it be positive, negative, or anything in between.

1. Choices & Decisions

• Mac Pro 2019: It's what I had available to me.
• W6900X: It's what I had available to me.
• W6800X Duo: It's what I had available to me.
• Ubuntu LTS: The ROCm-supported OS family I am most comfortable with. Alternative: RHEL
• Ubuntu 24.04 LTS: The latest Ubuntu LTS version supported by ROCm at the time of writing. Alternative: Ubuntu 22.04 LTS
• Ubuntu Server: To avoid desktop overhead and keep the system headless. Alternative: Ubuntu Desktop LTS
• Data Room: I placed the Macs in a Data Room, so I don't hear the loud fans. Alternative: Place it at your desk, or anywhere else.
• DRM/AMDGPU: I opted to use the GPU driver in the kernel, to patch it to support the Infinity Fabric Link Bridge. Alternative: Install DKMS and AMDGPU.
• Kernel: Patched Ubuntu 6.17 HWE kernel, based on Ubuntu’s linux-hwe-6.17 source package, to support the Infinity Fabric Link Bridge. Alternative: Standard Ubuntu kernel.
• ROCm: AMD’s CUDA alternative for AMD GPUs. Alternative: Vulkan
• ROCm 7.2.3: Latest ROCm that supports my GPUs at the time of writing. Alternative: Outdated ROCm.
• vLLM: Concurrent utilization of loaded LLMs. Alternative: Ollama & Llama.cpp
• Hermes Agent: More tool-savvy and self-learning. Alternative: OpenClaw
• GitHub: All my files and commands have been uploaded to GitHub, to make this guide shorter than 40,000 characters. Alternative: Multiple Guides...

Please let me know if the GitHub links do not work.

These are the choices I made, and I am still refining them. They work for me. Keep in mind that this is all held together with the digital equivalent of duct tape. If you change anything, it may or may not work. If you do, I would genuinely appreciate hearing what you tried, what worked, what failed, and why you changed it.

2. Setting up Ubuntu after Installation

Step 00: Infinity Fabric Link (Jumper & Bridge)

Please remove the Infinity Fabric Link Jumper(s) or Bridge from the GPU. Ubuntu 24 kernels do not currently support it, as of 6.17.

Specifically, with kernel 6.8, none of the GPUs will work. When upgrading to 6.17, only one GPU will work.

If you have an Infinity Fabric Link Jumper or Bridge, follow the patch section later in the guide to make it work with your GPUs.

Step 01: Update, Upgrade, and Tweak the System

What we will do:

• Change ubuntu.sources from http to https
• Attach to Ubuntu Pro (This is optional, and requires interaction)
• Update & Full-Upgrade
• Upgrade to the latest HWE kernel
• Remove cloud-init
• Make all Ethernet ports accept DHCPv4 automatically
• Modify Grub to include "loglevel=7 log_buf_len=16M iommu=pt" kernel flags
• Reboot

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/2.%20Setting%20up%20Ubuntu%20after%20Installation/Step%2001%3A%20Update%2C%20Upgrade%2C%20and%20Tweak%20the%20System" | bash

Step 02: Install T2 Linux Repository

Since we are using a Mac Pro 2019, which is a Mac with a T2 chip, some additional packages are required to be able to properly communicate with the hardware.

What we will do:

• Set up the T2 Ubuntu 24 (Noble) Repository
• Install 3 Packages: applesmc-t2 apple-bce t2fanrd
• Reboot

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/2.%20Setting%20up%20Ubuntu%20after%20Installation/Step%2002%3A%20Install%20T2%20Linux%20Repository" | bash

Step 03: Enable T2 Fan Daemon

After installing the T2 packages, the command below is used to activate the fan service.

What we will do:

• Enable the t2fanrd systemd service

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/2.%20Setting%20up%20Ubuntu%20after%20Installation/Step%2003%3A%20Enable%20T2%20Fan%20Daemon" | bash

Step 03-Optional: Set Fans to Maximum

I do not trust Apple Cooling. I would rather the fans wear out and replace them for a few dollars, versus the GPUs (especially the Duo models) being damaged due to overheating.

What we will do:

• Set all 4 fans to maximum speed

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/2.%20Setting%20up%20Ubuntu%20after%20Installation/Step%2003-Optional%3A%20Set%20Fans%20to%20Maximum" | bash

Step 04: Download and Install ROCm 7.2.3

This section will install ROCm 7.2.3, but it will NOT install dkms or amdgpu drivers. I opted to use the kernel driver, drm/amdgpu, so I can later patch it to support the Infinity Fabric Link Bridge.

What we will do:

• Make a new directory to save all downloaded files
• Download ROCm installer
• Install ROCm Dependencies
• Install ROCm
• Give all users access to ROCm
• Add ROCm to path
• Show you a bunch of output displaying your GPUs, which are working with ROCm or the driver, etc.
• Reboot

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/2.%20Setting%20up%20Ubuntu%20after%20Installation/Step%2004%3A%20Download%20and%20Install%20ROCm%207.2.3" | bash

Step 05: Install Python Tools

We will be using Python and pip to install several packages for local AI. The following commands are to set up the correct versions, as well as some quality of life choices.

What we will do:

• Install these packages: 2to3 python-is-python3 python3-pip python3-venv python3-dev python3-setuptools
• Install or upgrade these packages, system wide: pip wheel setuptools
• Install numpy 1.26.4 specifically, system wide

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/2.%20Setting%20up%20Ubuntu%20after%20Installation/Step%2005%3A%20Install%20Python%20Tools" | bash

Step 06: Install PyTorch & Other ROCm Related Wheels

Not everything here is needed for everyone. I included what I could, what worked, and what had some value to some local AI use case.

What we will do:

• Install PyTorch Wheels
• Add AMD ROCm APT Repository
• Set AMD ROCm Apt Repository at priority 700 (Higher than Ubuntu)
• Fix some ROCm Symlinks conflicting with MIGraphX
• Install MIGraphX & Half packages
• Install ONNX Runtime package
• Install TensorFlow ROCm package
• Install Apex Wheel
• Clean up packages
• Reboot

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/2.%20Setting%20up%20Ubuntu%20after%20Installation/Step%2006%3A%20Install%20PyTorch%20%26%20Other%20ROCm%20Related%20Wheels" | bash

Step 07: Verifying Everything

We just completed installing everything in the standard way. We just need to verify that everything is now set up correctly.

What we will do:

• Give you several boxes showing the status of everything we just set up

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/2.%20Setting%20up%20Ubuntu%20after%20Installation/Step%2007%3A%20Verifying%20Everything" | bash

3. Infinity Fabric Link Jumper / Bridge

AMD released several GPUs specifically for the Mac Pro 2019 that support their Infinity Fabric.

These GPUs and the Infinity Fabric Links are discussed in these posts:

• AMD Radeon Pro Vega II Duo and Infinity Fabric Link
• Linux on Mac Pro 2019: Infinity Fabric Link, Multi-GPU, and the Current State of AMD XGMI Support

The first set of GPUs that support it were the AMD Radeon PRO Vega II & Vega II Duo. The PC equivalent is an AMD Radeon PRO VII, which also supports an Infinity Fabric Link.

The second set of GPUs are the AMD Radeon PRO W6800X, W6800X Duo, and W6900X. These GPUs are in the Sienna Cichlid family of GPUs. Also referred to as RDNA2.

At the announcement of the Sienna Cichlid family, these GPUs were marketed as supporting xGMI. The Infinity Fabric Link is the physical bridge / jumper. xGMI is the software path that allows the GPUs to communicate over that link. However, on release, only the Apple MPX GPUs actually supported the Infinity Fabric Links, while the standard versions did not.

This might explain why support for xGMI on Sienna Cichlid was added between 2019 and 2020 to the Linux kernel drm/amdgpu, but later removed in 2022.

Many of us here in the subreddit tried to figure out the problem with the Infinity Fabric Link, and tried to find a solution to it. One such redditor actually cracked it; creating a patch to the current kernel drm/amdgpu driver, which through my testing seems to have completely solved the Infinity Fabric Link regression that happened in 2022.

You'll need to keep in mind that this is just the first step. While we are moving forward, there is still the question of ROCm support, HIP support, and everything else.

Step 01: Download, Build, & Install the Patched Kernel Files

Let's start. We will do the following:

• Make a directory to download kernel source
• Install packages required to patch the kernel
• Activate the source to download kernel source
• Patch drm/amdgpu
• Build a full patched kernel
• Install the patched kernel

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/3.%20Infinity%20Fabric%20Link%20Jumper-Bridge/Step%2001%3A%20Download%2C%20Build%2C%20%26%20Install%20the%20Patched%20Kernel%20Files" | bash

With this, you are now the proud user of a patched kernel that supports the Infinity Fabric Links on the Sienna Cichlid MPX GPUs.

At this point, shut the system down, reinstall the Infinity Fabric Link Jumper or Bridge, then boot back into the patched kernel.

Step 02: Verify Patched Kernel & GPU Initialization

We should probably run a verification one last time. Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/3.%20Infinity%20Fabric%20Link%20Jumper-Bridge/Step%2002%3A%20Verify%20Patched%20Kernel%20%26%20GPU%20Initialization" | bash

While more testing is still needed, this is quite the achievement for the community. Thank you again, anonymous redditor.

4. AMD Duo MPX GPUs and Setting BAR Correctly

I have been using my Mac Pro 2019 with Dual AMD Radeon PRO W6800X Duo for local AI inference for some time now, and I have not had any BAR-related problems. However, since I moved from using Proxmox to having Ubuntu 24 on bare-metal, I have started noticing some BAR warnings and errors.

It seems that this problem may come from the way the Mac Pro firmware allocates PCIe resources before Linux takes over, specifically when using Duo MPX GPUs.

One redditor, whose account is now deleted, shared a GitHub link to what I can only describe as someone's documentation of how he fixed the BAR issue on Vega II Duo GPUs. I have dubbed this the nbritton's method.

Our goal now is to use nbritton's method, adapted for the W6800X Duo. I tried to make it also work as a copy and paste solution for the Vega II Duo as well, but I have not tested it.

Warning: This changes GPU driver load order and PCIe BAR allocation behavior. If something goes wrong, you may need to boot from a recovery kernel, remove the service, or undo the GRUB changes. Also, note that SGLang's AMD GPU documentation recommends pci=realloc=off iommu=pt, which conflicts with nbritton's method because nbritton's method depends on PCIe BAR reallocation behavior. In other words, pci=realloc must not be disabled for this method.

Let's start.

We will do the following:

• Blacklist amdgpu
• Add pci=realloc to grub
• Configure resize-gpu-bars.service
• Set up nbritton's method files

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/4.%20AMD%20Duo%20MPX%20GPUs%20and%20Setting%20BAR%20Correctly" | bash

5. Finalize the Infrastructure

After completing the linked sections above, we should have:

• Install Ubuntu (You did this on your own or using a previous guide)
• Prepare Ubuntu's environment
• Set up T2 related environment
• Installed ROCm
• Installed PyTorch and several other local AI optimizing software
• Patched the kernel (linux-hwe-6.17, source 6.17.0-29.29~24.04.1) to support xGMI and the Infinity Fabric Link Bridge and Jumper.
• Set up nbritton's method for Duo MPX GPUs BAR correction

Once you're done, please reboot to make sure everything sticks. Then repeat step 07: Verify Everything, above to verify everything is correct and as it should be.

6. Local AI

Now that the infrastructure is ready, it's time to move to our frameworks of choice.

While I definitely plan to expand, I have focused mainly on text generation. When I first started, consideration was Ollama, Llama.cpp, and vLLM. I see new options now, such as SGLang as well.

I am excited to share that vLLM supports this setup and works well. I hope to release a separate guide for it soon.

For the purpose of this guide, I will continue with Ollama, for the simplicity of it, and a Hello World type scenario.

Step 01: Install and Configure Ollama

We will do the following:

• Set up Ollama
• Fix ollama.service vs. ollama serve separate model libraries

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/6.%20Local%20AI/Step%2001%3A%20Install%20and%20Configure%20Ollama" | bash

Step 02: Verify Ollama Setup

We will do the following:

• Verify Ollama services and data folders permissions

Copy the following command into your command line interface of choice:

curl -fsSL "https://raw.githubusercontent.com/FaisalBiyari/MacPro2019LocalAI/refs/heads/main/Reddit/Mac%20Pro%202019%20Local%20AI%20Guide%3A%20Ubuntu%2024.04%2C%20ROCm%207.2.3%2C%20PyTorch%202.10%2C%20and%20Infinity%20Fabric%20Link/6.%20Local%20AI/Step%2002%3A%20Verify%20Ollama%20Setup" | bash

Step 03: Download and Run Models

We will do the following:

• Download and run our first model

Copy the following command into your command line interface of choice:

ollama run qwen3.5:0.8b --verbose

You can find more models on Ollama's website. Below are some other models I am considering:

ollama pull qwen3.6:27b
ollama pull gemma4:31b-it-q4_K_M
ollama pull granite4.1:30b
ollama pull medgemma:27b
ollama pull mistral-medium-3.5:128b
ollama pull gpt-oss:120b
ollama pull qwen3.5:122b
ollama pull nemotron-3-super:120b

7. Done

With this, we are done with this guide.

It has been a long journey setting up this infrastructure, and preparing for the actual goal.

My testing was done on Mac Pro 2019 systems with dual W6900X MPX modules and dual W6800X Duo MPX modules. I have not tested this with Vega II or Vega II Duo MPX GPU modules.

Next, I plan to focus on vLLM for a while. Optimization, quantization, and automation of operations.

After that, I hope to dive into Hermes Agent by Nous, with the hope of building multiple agents around a few local models run on vLLM, communicating and working together.

Expanding to images or vision, as well as to voice, is also down the pipeline.

The possibilities are endless. I hope to hear what everyone else experiences with this guide and with local AI in general: what worked, what failed, what workloads you are running, what use cases you care about, what problems you hit, and what solutions you found.

Looking forward to seeing how everyone takes advantage of this guide, and local AI.

8. Credit

Credit where credit is due. A lot of the information here was gathered from the community in bits and pieces.

I do want to take the opportunity to thank the anonymous redditor for his/her contribution (creating the whole kernel patch). THANK YOU!

• Nikolas Britton for the nbritton method, fixing the BAR issue on the AMD Duo MPX GPUs.

• u/AdityaGarg8 for always being supportive, no questions asked.

• My AI of choice, for the support through all of this.

• r/MacPro2019LocalAI redditors, for keeping in touch, and motivating me to continue going. You guys are the real MVPs.

---

Disclaimer: I wrote this post myself. I also used AI as a tool to help clean up the wording and formatting.

Resources:

• GitHub Repository hosting these guides.

is there any option to do it ? and I have another question if I can do two partitons, one for Linux another for MacOS is it possible? If it is how can I do it?

Hello all.

I have a mid-2011 MacBook Air that has a BCM943224PCIEBT2 (Broadcom) WiFi adapter.

After installing Mint xfce, the system locks up when it boots up.

If I remove the Broadcom hardware from the motherboard and attach a usb nic, the system works just fine. I can install apps and browse the web just fine.

If I put the Broadcom adapter back in and power it up, the system locks up again.

I suspect it’s a driver issue but don’t know how to resolve.

Any help or insight would be appreciated.

I could just recycle the laptop but now I want to win this battle. lol.

Thank you.

Hello guys I have recently bought an MacBook 12 for almost nothing from marketplace.

I was thinking of installing Linux to play around and maybe ssh into an ec2 if I want something more powerful.

The real limitation is that I am not sure how how to proceed with the installation and which distro to choose.

Has anyone used Linux on MacBook 12 and if so which one would you suggest ?

I did the whole OpenCore Launch Patcher to get Sequioa on my old ass 2015, 8 GB RAM , and 512GB ssd..

Its intel i5 dual core version.

Sequioa runs .. alright? Like kinda slow tbh

Would Linux XFCE work out better? I'm scared since I'd need this for school lol.

I want to know if I'd still be able to use Bluetooth for my earbuds so i can listen and talk during my online lectures.

I'll be doing nursing program (where most lectures will be online and other half is lab intensives on campus).

Worth it to try to get linux mint on it or just get a new macbook air m5?

Does anybody know how to undervolt a Mid 2015 Macbook Pro (11,4) on arch linux? I tried intel-undervolt but it didn't work. The configs were applied but it had no effect on temperatures. I'm trying to do this to lower CPU temps while gaming competitively. Thanks.

estou entrando numa empresa que utiliza 98% linux, e sou muito leigo nesse sistema operacional. gostaria de mudar o sistema por completo com a finalidade de estudar redes e continuar a programar. queria saber uma disto boa para isso.

MacBook Pro 2015 Monterey

2,5 GHz Intel Core i7 Quad-Core

16 GB 1600 MHz DDR3

APPLE SSD SM0512G

I got a 2015 macbook pro 8gb ram , 128gbSSD with only 300 charge cycles... this thing is def brand new feeling. who runs Ubuntu on here and whats your thoughts on it?

Last year I got iMac from 2013 that I got from my cousin. It has a Intel core i5 and Nvidia gt 750m and it has 8gb of ram and 1tb hard drive. Since I cannot afford SSD. What is the most stable and fast Linux distro that I can possibly get...

Having experimented a lot with Linux on Mac the following points are dealbreakers for me. Currently using Ventura (pre 2015 Macs) or Sequoia (post 2015 Macs), with OCLP, and will continue to do so until they are scrapped:

• Linux isn't actually faster. I see no evidence of this - comparing fresh install to fresh install
• Suspend doesn't work, or loses a lot of battery
• Instant wake gone
• Speakers sound worse, and the only real solution is buying an expensive reference microphone and building your own speaker correction profile
• Weird problems with T2 Macs like flashing touchbar
• Apple built the best machines in the world around mediocre hot processors (Intel)

Unless your Mac is extremely old I just don't see the point of Linux. The latest web browers still work on Ventura, and Sequoia. The only possible advantage might be security, but you're probably not installing a bunch of random software on an old Mac, and the browser itself should protect from online exploits.

Probably a wider point is how sensible it is to keep using the same computer for decades. Any machine without usb-c ports is already a bit annoying in the modern world. Not to mention improvements in WiFi standards, screen technology, etc.

Having used ARM chips (Apple and Qualcomm) on Mac, Windows, and Linux with their amazing low latency and battery life, the future is ARM.

I have the following Mac laptop on extended loan from a work situation and there may be some chance I can just keep it or maybe buy it as my work ends. This is the machine:

• MacBook Pro (13-inch, 2016)
• i5-6267U CPU 2.90Ghz
• 8 GB 2133 Mhz LPDDR3
• Graphics Intel Iris Graphics 550 1536 MB

I had been planning on buying a used PC, something like an 8th gen i7, and using Linux on it...but if I can keep this computer, maybe I don't have to. It's only a 6th gen Intel, but maybe it will work for my purposes, which are:

• Recording and mixing my own music. 2-20 tracks, maybe 1-3 digital instruments, MIDI, acoustic tracks with some effects on most tracks. I need it to be quiet while recording acoustically and not have drop outs when mixing larger projects, but it's not like I'll be doing super intense orchestral stuff.
• Everything else is just "basic computer use" (web, YouTube, writing, spreadsheets).
• No gaming.

I'm concerned that I might be fighting it to get Linux to run well on it. I want a no hassle computer life. I'll be using it with an external 24" monitor and probably using Fedora KDE on it.

Opinions? Thanks in advance.

Being new to the linux community I see a lot of people saying they don't like snaps this and that.. so instead they enable flatpaks or download the deb versions which I agree with in most cases like I needed slack so I just went and got it from the website long story short I was stuck doing brave tweaks messing with flags, extensions etc finally got tired of it and used Firefox through snaps and twitch works beautifully!!! I never knew Firefox through snaps is already optimized for your hardware through cannicol or whatever its called ? I just think its funny I tried for days to get brave to run twitch at 1080p and Snap firefox just runs it effortlessly I am on a 2015 macbook pro btw 8gb ram 2.7 processor speed. I now will embrace snaps lol

I've got an old 2013 MacBook. It's only got 256GB of storage, most of which was just taken up by Mac OSX Catalina. No program supports that OS anymore, and updating it means losing more storage space, so I decided it's time to try Linux!

I downloaded Fedora 44 KDE Plasma, installed it, and realized I have no WiFi. Welp.

Googling it, most "fixes" require going on the internet to download or update some packages via the terminal. But how? USB tethering via my phone worked only once - after rebooting, it never worked again. And apparently my TP-Link USB WiFi dongle is ALSO not supported.

I tried going on some RPMFusion website (I don't even know what that is for), downloaded free and nonfree repositories (??), but when I try to open them, they just open the Settings, and they do nothing - or they error and say they can't update. I lost track of what I did and DIDN'T do just to try and get stuff working.

So now I'm stuck. No WiFi, no bluetooth (at first boot, it did have BT, strangely), no audio.

What can I do? Is there a driver I can simply download from another computer and put that on the MacBook? I'm pretty close to regretting this decision.

EDIT: FIXED!!

What I did:

• Upon first install, use USB tethering (rebooting at this point screws it up)
• Install the RPM Fusion Free repository
• Install the RPM Fusion Non-free repository
• Update via DNF
• Reboot
• Install broadcom-wl
• Reboot

We all have that one old, faithful friend. Mine is a 2011 MacBook Air. It has a slim aluminum body, a stylish design, and an excellent backlit keyboard, but it came with a "sentence" from Apple: only 2 GB of RAM that cannot be upgraded. Modern macOS turned it into a "brick" that would freeze for a minute with every click.

However, I decided it was too early to consign it to the scrapheap of history. The solution was found where enthusiasts always look: the world of open-source software.

Linux Mint: A Breath of Fresh Air I wiped the heavy, sluggish macOS and installed Linux Mint MATE. Why this one? Because it’s lightweight, intuitive, and works "out of the box," even on Apple hardware. But let’s be honest: even the lightest Linux distribution with a modern Chrome browser will quickly hit the ceiling of those 2 GB of RAM.

To make my Air truly fly, and not just "exist," I had to assemble a secret puzzle of three technologies.

zRAM: Air Out of Thin Air The first hero is zRAM. Imagine your RAM is a small suitcase. Previously, when you had too many things, it simply wouldn't close (and the system would hang). zRAM acts like vacuum bags. It takes the data, compresses it right inside the RAM, and allows you to cram two or even three times more information into the same bag.

But when even the compressed "bags" fill up the space, our trump card enters the scene.

Swapspace: Dynamic Intelligence A standard swap file in Linux is a blunt, clunky chunk of disk space. It either wastes space on the SSD for no reason or isn't there when you need it while opening your tenth Chrome tab.

Swapspace is like a manager with built-in artificial intelligence. It monitors my MacBook's pulse:

• While there is enough memory, it doesn't take up a single byte on the disk.
• As soon as the "free energy" level drops below a critical percentage, it instantly begins "carving out" space on the SSD in neat, pre-defined chunks.

It’s as if your laptop, in moments of heavy fatigue, started quickly building extra temporary warehouses, and then dismantled them just as fast once the work was done.

My Rescue Formula: On my 2011 MacBook Air, I set up a multi-layered defense:

1. RAM: Works at the limit, but is protected.
2. zRAM (First line of defense): Compresses everything possible to maintain speed.
3. Swapspace (Second line): A safety net on the disk that unfolds only when there is a real threat of a crash.

In the config, I set a threshold of 10% (lower_freelimit). That is the exact line where the magic begins. The system doesn't wait for the memory to reach "clinical death"; it starts acting in advance.

The Result: The Old Horse Still Pulls the Plow When I look at the terminal and see how Linux Mint smoothly juggles data between zRAM and dynamic swap files, I realize: my MacBook Air still has some fight left in it. I can comfortably write code, watch videos, and open the million tabs I need.

This isn't just optimization. It’s a philosophy. Why buy a new laptop for browsing when a beautiful old MacBook Air running Linux Mint can work faster and more reliably than many modern budget laptops?

https://preview.redd.it/dp6o3sfwbj0h1.png?width=672&format=png&auto=webp&s=dedfbdbefaa436f2bb613f6d4b07d65eca45a30d

https://preview.redd.it/u880zbgwbj0h1.jpg?width=1440&format=pjpg&auto=webp&s=b6299fd2f49e80bef06803c8a9deea2010c19f66

Hello People,

I bought a MBP late 2013. It has intel i5 4 GB of RAM. have a question, Has anyone tried changing the Mainboard?

I want to switch to an i7 Processor with 16GB RAM.

I saw some people faced problems with the display after changing it.

Looking for some suggestions.

TIA 😃