So there are a zillion of these, including ones that do what yours does. But that being said, I'm going to always upvote every single one of them because this is better and more important that what the big companies are doing across the board.
Thank you! Would love to hear which ones you've used. Working with local files without anything going to the cloud was the main thing I wanted. I tried Jan, OpenWork, Chatbox and Lobe, and couldn't get that working well in any of them. If there's one I missed it would be great to check it out!!
Have you tried Open WebUI? It doesn't determine which model works best for your hardware, but it otherwise has a very large feature set with a large community, and runs offline by default. Geared more for technical users, however.
It feels like the last mile is so long in this space. I'm a SWE with a ton of experience and I still haven't gotten over the decision paralysis of figuring out which model to run locally, and which inference platform should I use, and will my M1 Macbook Pro actually run anything well enough to be useful, and on and on.
It's kind of embarrassing to admit, but having something Just Work(tm) makes getting started so much easier.
It’s a huge new subject area and it’s completely exhausting to learn. I still feel like a total novice.
I have an M1 Max (more memory bandwidth) so I am not sure how much advice I can give about models, but I would suggest maybe trying the new LFM2.5-24B-A2B. It’s surprisingly good. If you want to mess about with multimodal work, Gemma 4 12B is really impressive. (I mostly use Muse Glimmer but it might be rather slow on an M1 Pro)
If you want to have the space to learn the terminology, tinker with what you can control etc., then you have three easy options: LM Studio, Unsloth Desktop or the llama.cpp native Mac app. But don’t get put off by the llama.cpp command line; most of these tools are running it behind the scenes, and most entries on Hugging Face have recommended parameters.
MLX is an option but so far I haven’t found it to have an edge over simple GGUF on Metal on the M1 at least; it seems it might have more advantages on the later M series chips, but it is usually slower for me.
I have explored running OpenCode inside a VM (you can “remote into it” from the OpenCode GUi desktop app). You might want to look at Paseo, which can do a similar thing but with many more coding agents.
I am quite intrigued by Osaurus; on macOS 26 and up it looks like it will manage a container for you.
You might also want to look at Orchard. Not done this myself yet but I can see the appeal.
I am an experienced web dev in my fifties. Six months ago everything I have written above would have been total gibberish to me. Learning some of the open weights stuff has made me feel much less helpless than I think I might if I just developed a Claude dependency. Nothing matters more to me than grasping the fundamentals.
I still don’t really use LLMs for hands-off coding. But I have found that a local LLM can be a useful sidekick; even at the most basic level it’s a better Google that remembers the context of queries.
Fwiw, I'm liking the koboldcpp "ecosystem", including koboldlite; basically it's letting me try a little of everything, though there may be something of a "jack of all trades master of none" thing going on. But it has these nice little presets for, e.g. llms, voice, music, images, a "chatgpt"-esque interface, etc.
Looks great. One thing I am missing is the ability to change the installation directory for the models. For space reasons, I want them to be on a different partition.
Linux. I saw you support HOB_USER_DATA, which is great. But I want my config to remain in .config/Hob and only move the models (or whatever else needs lots of space) to another disk/directory.
Edit: Actually I think HOB_USER_DATA is enough for my use case.
It's still pretty tricky to do this as a solo dev to keep feature parity in my experience (fun fact, even Claude's own Desktop app is made in Electron).
That being said, majority of the heavy LLM lifting happens natively with llama.cpp :)
I'm actually building something similar and thank you very much for sharing you gave me a few inspirations. I want mine to integrate seemlesly with an animated Ai companion (it's harder than it sounds haha). Anyways great stuff! Gave it a star.
Haven't tried it yet, but I like that you shared your process in such an honest way, and kept it no frills, as in no LLM wall-of-text readme in the repo. Wish we could see that more often these days.
“Garth is the most significant artist that I've worked with and I've worked with Lulu and four other people, so we’re talking crème de la crème.” — Dean Learner
I did not enjoy that there was no way for it to clean up the 18GB of models it installed after I determined it was not really usable for any real work.
With the raise of AI, I believe: open-source and local software's will be on the rise, but with the open-source environment there is a real security issues that rise.
Never the less, really appreciate your contribution
jrm4 | 12 hours ago
[OP] pancomplex | 12 hours ago
universenz | 11 hours ago
fmxexpress | 11 hours ago
prophesi | 11 hours ago
dfltr | 7 hours ago
It's kind of embarrassing to admit, but having something Just Work(tm) makes getting started so much easier.
dofm | 6 hours ago
It’s a huge new subject area and it’s completely exhausting to learn. I still feel like a total novice.
I have an M1 Max (more memory bandwidth) so I am not sure how much advice I can give about models, but I would suggest maybe trying the new LFM2.5-24B-A2B. It’s surprisingly good. If you want to mess about with multimodal work, Gemma 4 12B is really impressive. (I mostly use Muse Glimmer but it might be rather slow on an M1 Pro)
If you want to have the space to learn the terminology, tinker with what you can control etc., then you have three easy options: LM Studio, Unsloth Desktop or the llama.cpp native Mac app. But don’t get put off by the llama.cpp command line; most of these tools are running it behind the scenes, and most entries on Hugging Face have recommended parameters.
MLX is an option but so far I haven’t found it to have an edge over simple GGUF on Metal on the M1 at least; it seems it might have more advantages on the later M series chips, but it is usually slower for me.
I have explored running OpenCode inside a VM (you can “remote into it” from the OpenCode GUi desktop app). You might want to look at Paseo, which can do a similar thing but with many more coding agents.
I am quite intrigued by Osaurus; on macOS 26 and up it looks like it will manage a container for you.
You might also want to look at Orchard. Not done this myself yet but I can see the appeal.
https://orchard.andon.dev/ai.html
I am an experienced web dev in my fifties. Six months ago everything I have written above would have been total gibberish to me. Learning some of the open weights stuff has made me feel much less helpless than I think I might if I just developed a Claude dependency. Nothing matters more to me than grasping the fundamentals.
I still don’t really use LLMs for hands-off coding. But I have found that a local LLM can be a useful sidekick; even at the most basic level it’s a better Google that remembers the context of queries.
ajvs | 11 hours ago
l3x4ur1n | 10 hours ago
jrm4 | 10 hours ago
vorticalbox | 12 hours ago
https://lmstudio.ai/
laughing_snyder | 11 hours ago
universenz | 11 hours ago
laughing_snyder | 11 hours ago
[OP] pancomplex | 11 hours ago
laughing_snyder | 11 hours ago
Edit: Actually I think HOB_USER_DATA is enough for my use case.
_aavaa_ | 11 hours ago
[OP] pancomplex | 11 hours ago
That being said, majority of the heavy LLM lifting happens natively with llama.cpp :)
eecks | 10 hours ago
Do you have examples of what hardware runs what models?
rhedak | 10 hours ago
[OP] pancomplex | 10 hours ago
mickelsen | 10 hours ago
[OP] pancomplex | 9 hours ago
atmanactive | 8 hours ago
[OP] pancomplex | 8 hours ago
atmanactive | 6 hours ago
ourcat | 8 hours ago
[OP] pancomplex | 7 hours ago
dofm | 7 hours ago
wilg | 6 hours ago
[OP] pancomplex | 5 hours ago
wilg | an hour ago
arkdezin | 6 minutes ago
Never the less, really appreciate your contribution