Hue does support Matter. Hue is expensive but delivers a premium experience, unlike the products talked about in this thread that are expensive but not better than the competition.
Got any you'd recommend? I've been paying the Hue tax because they're the only bulbs I've had with zero connectivity issues ever across several years, whereas every other brand I've tried has been very unreliable.
I use Bazzite for development bc it works like a Mac with sane defaults and a just works approach:
- IDEs are no problem. Editors will "just work" for anything you type into the app store - Bazzite handles the special cases for you and installs them through brew taps or Flatpaks.
- For development it's basically just like a Mac where you also can't install system-level packages: Node, Python etc work through brew / nvm / uv same as on Mac. Development that involves containers will be unchanged from a Mac. For compilers specifically, same as on Mac: Install it through brew, or if you need a Debian or Fedora base you do `distrobox create` and you can apt-install in a transparent podman container.
Having read above article, I just gave llama.cpp a shot. It is as easy as the author says now, though definitely not documented quite as well. My quickstart:
Go to localhost:8000 for the Web UI. On Linux it accelerates correctly on my AMD GPU, which Ollama failed to do, though of course everyone's mileage seems to vary on this.
Was hoping it was so easy :) But I probably need to look into it some more.
llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'gemma4'
llama_model_load_from_file_impl: failed to load model
Edit: @below, I used `nix-shell -p llama-cpp` so not brew related. Could indeed be an older version indeed! I'll check.
As it has been discussed in a few recent threads on HN, whenever a new model is released, running it successfully may need changes in the inference backends, such as llama.cpp.
There are 2 main reasons. One is the tokenizer, where new tokenizer definitions may be mishandled by the older tokenizer parsers.
The second reason is that each model may implement differently the tool invocations, e.g. by using different delimiter tokens and different text layouts for describing the parameters of a tool invocation.
Therefore running the Gemma-4 models encountered various problems during the first days after their release, especially for the dense 31B model.
Solving these problems required both a new version of llama.cpp (also for other inference backends) and updates in the model chat template and tokenizer configuration files.
So anyone who wants to use Gemma-4 should update to the latest version of llama.cpp and to the latest models from Huggingface, because the latest updates have been a couple of days ago.
I just hit that error a few minutes ago. I build my llama.cpp from source because I use CUDA on Linux. So I made the mistake of trying to run Gemma4 on an older version I had and I got the same error. It’s possible brew installs an older version which doens’t support Gemma4 yet.
And that's exactly why llama.cpp is not usable by casual users. They follow the "move fast and break things" model. With ollama, you just have to make sure you're getting/building the latest version.
Its not possible to run the latest model architectures without 'moving fast'. The only thing broken here is that they are trying to use an old version with a new model.
I'm a bit unsure what that has to do with someone running an outdated version of the program while trying to use a model that is supported in the latest release.
It's a new-ish project FYI. But to answer your questions:
- Apps: It's Linux (like desktop or server), but "image-based" so you install apps in containers like iOS or Android do (and therefore OS updates basically-never break). https://flathub.org is generally the main app store for Linux containerized phone apps.
Nitpick regarding apps: https://flathub.org/en/apps/collection/mobile/1 is the better link IMHO, even if not all apps in it do actually perform great on mobile [0], and some apps that work well on Mobile are not part of the collection due to lacking some bits in app metadata [1]. Help with sorting this out is very much welcome :-)
Updating without worries has made it much more daily-drivable for me on a Oneplus 6 (ie. it has rollbacks and image-based updates), despite being so new. It's fun that image-based OSs - which were arguably popularlized by phones - are now coming back to phones on the Linux side too.
