Does anyone run their own AI service?
If so,
Which one?
What hardware?
Do you have a way to access it from outside or from a phone?
And, if you’re open to sharing, what do you do with it?
I know AI-enabling hardware is insanely expensive right now, but some of the smaller (<32GB) more efficient models (think deepseek- or qwen-based) don’t absolutely need specialized hardware to run and perform well enough for many purposes.
I am so aware of the absolutely abysmal privacy practices of basically all AI companies that I’m not comfortable using them to help me with web searches and the such, because there’s no way that all this information won’t be going into a profile. This makes me want to have my own “helper” service.
Very similar, but I’m using Gemma4 12b. I could run 26b but that would exhaust my vram after a short interaction. And ollama. Open WebUI + Home Assistant hooked up with it, a couple very basic scripts I threw together, and connected to Kagi.
I’m trying to get my folks off the Gemini/Google bandwagon for the privacy aspect, but also because it’s just cool from a tech geek perspective. For me, any questions throughout the day that I want info on, but not enough to do a deep-dive for an hour+, gets fed to Steve, my models name. Or I’ll use it as a springboard and then properly read the citations for more info. And I feed it HA automations when I get stuck scratching my head on an edge case or whatever - it’s alright but helps me explain what I want from the automation, and when it understands my goal, great, and when it doesn’t I reflect on what I have setup and can usually go ‘ah ha’ and fix the issue. It’s like a rubber ducky/pair programmer that you can both think is an idiot sometimes, but it doesn’t judge you when you’re the idiot.
That’s a pretty good way to describe those kinds of models. Somewhere between rubber duck debugging and a really lazy intern. Better than an algorithm, faster than a human, but less trustworthy than an intern. It’s great if you know how and when to use it. Maybe it’ll become an intern soon enough, but for now let’s focus on decompiling adobe into bankruptcy.
What’s your rig?
1070ti and some hexacore something cpu that’s alright with around 24gb ddr4, I think one of the slower speeds. I also got a faster PC with another llama.cpp instance and I vibe coded a quick and dirty proxy which I can use to switch between the different backends. It’s genuinely useful because I got code editors but also my Open-WebUI using it.
Sounds elaborate but generally it’s all pretty primitive.
Also fyi long preloading steps because my vram is obv not good enough to hold the full model and kv cache and stuff, generation at about 15t/s tops.
My experience is right now we’re at the stage where it’s a good assistant but not great for actually taking over bigger tasks completely.
Am looking forward to:
Random Question, I’ve been trying to offload some of my stuff handled by claud to basically this exact setup. However one of the things I manage has a pair of MCP servers that are required. I might not be smart enough, but how do you get Qwen to use an MCP?
MCP is a really dumb server that just takes requests and sends back data.
Somewhere in your frontend settings (Open-WebUI has it under “integrations” I believe, some backends can set these things too) you see a section called “MCP server”. You need to keep your MCP server running somewhere (it’s very slim, so not a huge deal usually) and then in those settings you put your IP and port for the server, for example “http://192.168.1.15:8080/”. Usually if you did it right (sometimes you can check if it works in the settings), you can ask the model if it has access to the tools and it will tell you.
What’s happening in the background is that every conversation the AI does, it gets a short preamble with some context about what it can do, and if you connect web search, custom skills or an MCP server (it’s just skills but they are run through their own server basically), the AI sees all that in this preamble if it’s set up correctly. And then when it feels like it needs to use those tools, it will check the description on how to do that, and then it uses them.
Thank you, I’ll give this a go
Pretty much my setup as well. Though I’m using qwen3.8 27b-Q4_K_M under ollama. Everything running with docker. Add nginx and either a domain+port forwarding or zerotier/tailscale you’ve got an app you can get to from outside your house.
Right now not sure how I’m going to leverage it not probably to streamline my self hosted stuff, help with config mgmt and documentation, web page summarization, etc. we’ll see how it does, just got it setup yesterday
In case you are unaware, friends don’t let friends use ollama. The llama.cpp CLI has become pretty much equally easy to use, plus since you use Docker there’s no need to compile anything.
Edit: typos and missing words
Oh shit I wasn’t aware! Thanks for the heads up, I’ll swap to llama.cpp
Oh damn what a useful link. Gonna check out those orchestrators, maybe I can replace my janky ass proxy.
I’ve got similar running on my RX 7600 XT. It is not a great experience for interactive use, but fine for async tasks. I’m also running nemo-speak for live local dictation and meeting transcription.
Yeah running in the background type beat. Not gonna trust this with anything important but it’s great to have someone just do shit for you or get a second opinion.
Yah doing similar on 5060ti.
That’s gonna be quick af with the same models.
It is, i also use the gemma4b model on it for description generation for my immich photos and its super fast.