Do you host your own ML / AI / LLM? What do you use, and what do you use it for?
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I do, but I am becoming increasingly more disappointed as time goes on. Not just self hosted, llms in general. They sometimes help, but they mislead so many times and waste time that you don’t even notice. I think that’s the trap. When you succeed at a task, you become impressed but don’t notice how many times it failed doing a simple task. And as soon as you scratch the surface, you see how you would have done it differently and perhaps in a better way. Even just googling is bad. It does research for you, but it has no critical thinking and can’t decide what is better from the results it gets (other than google ranking) so it often leads you to think it did as good as you would, when it’s nowhere near as good. Every time I did the googling myself after it did, I did it much better. And I mean MUCH better. Ask it to find the app, it misses the most important ones, hallucinates a bunch, for ex. I found this to be the case with frontier models as well.
Self hosting has its benefits, but seeing how the ecosystem looks right now, concluding this is a huge bubble is inevitable. It reminds me of crypto so much. It looks rich and plentiful, but as soon as you dig a mm under the surface - nobody has tested it, it’s got a critical bug, it is overblown and there are issues with no response. No docs, no info, no nothing. For the biggest thing in technology in history, it is awfully hollow. I don’t mean it in a condescending way, in fact community is enthusiastic and very helpful, it’s just that it doesn’t live up to what most would expect.
A caveat I need to mention is I have not used it for coding - I have an irrational fear and resistance towards it, being a programmer. I just won’t touch it, even if it means the end of my career. I’m trying to be grown-up about it, but so far, I dont want to use it, for good and bad reasons.
Running qwen3.6 27b through llama.cpp.
It’s about as capable as sonnet 3.5.
I use it for light scripting, but real coding is done by cloud models.
I’m also using it as the brain for my Hermes agent. It sends me digests of news, subreddits, chats that I’d like to read but don’t have time for. It does a great job researching things on the web for me, too.
That’s a great model and it’s the one I use too.
Do you mean Sonnet 4.5?
I don’t have the rig to run it at real speeds but I’ve played with it over API. Seems pretty good.
No, it needs a lot more babysitting than 4.5 does. 3.5 was on the same level of mistakes, at least on the quants I have to use.
Yes, I got a Strix Halo machine before the RAM price hike and use it to run all my ML stuff on it.
Currently using llama-swap with llama.cpp/ComfyUI and opencode/Open WebUI as frontend.
I’m running Qwen3.6-27b, Voxtral Mini 4b, Piper and Qwen Image. Also, some embedding and reranking models.
I use them for:
- Tagging and classification of my documents in Paperless
- Home Assistant (voice assistant)
- Translations (both text and image)
- Transcriptions
- Some light coding and debugging
- Avatar/Backdrop generation for DnD sessions
What sort of tok/s are you getting on the strix?
About 200 t/s prompt processing and 10-20 t/s with MTP.
Greatly depends on the task, predictable things like code generates at 18-20 t/s. Creative writing more like 10-17 t/s.
Damn - I thought strix would do a bit better than that, for how much it costs.
Given the 27b is a dense model, I think the numbers are quite ok. Curious about the quant tho.
The cool thing about the strix is its large unified memory, but it lacks memory bandwith for compute intensive workloads. Something like Qwen3.5-122b MoE with only like 12b active parameters might run at twice the speed if it fits the configuration.
Curious about the quant tho.
Q8 from unsloth.
Something like Qwen3.5-122b
My go to model for knowledge. Definitely much faster at Q5 but it lacks the tool calling quality of the Qwen3.6 models. Really hoping we see a Qwen3.6-122b soon…
In case you missed the Ornith 1.0 release (Qwen and Gemma RL finetunes for agentic / coding workloads), they look interesting to bridge the gap until we see larger 3.6 models or a 3.7 release. I didn’t test them yet but according to benchmarks, the 35b MoE seems to be more or less on par with Qwen3.6 27b dense, while ofc a lot faster.
Yeah. Though I think theres a new strix out soon (Medusa? Gorgon? Something like that).
Its a bit like my P40. On paper, it has 24GB. But that 24gb is capped at 400GB/s and the ai compute is what…Pascal era?
AI = Good, fast, cheap - pick 2
Well compared to the strix, 400GB/s is not that bad, I think with fast system RAM and expert offloading you could squeeze quite something out of it when running stuff in the 100b-a10b regions.
Your bigger problem is going to be future software support.
No. I still have no use for it and everything I use is automated without at a far lower footprint.
Yep. https://lemmy.world/post/46066942/23416719 Basic setup, works for me
No, I’m not interested in that topic
If I wanted AI for some reason, it’d be self-host or nothing.
Hell naw my homelab is already sucking way too much power and running too hot.
Running decencored Qwen3.6-27b and a 9b Gemma for RAG and scrapes on Ollama with a mostly vibe coded discord bot. Just got it to run tools and scrape and post news on a schedule. The first model I can run locally that’s smart enough to be useful. May give Jan a try for the back end after reading that other guys rant.
Mostly use it for stupid questions I could have googled and to brag to friends.
I currently run Qwen3.6-27b on llama.cpp and use it via openwebui. Mostly, I use it for web research via tavily, to a lesser extent for coding and interactively learning about things that are new to me but common in training data (such as basic math or ML concepts).
No I don’t. Unforunetly using Claude (asking myself everyday why tf cuz I don’t do crazy shit) but trying to move on to LumoAI even meaby will buy a premium version to check this out formyself.
Yes, llama-swap and I use it for home assistant text-gen notifications, basic coding tasks, etc
If anyone here self-hosts definitely check out llama-swap as it has some nifty features for hotswapping LLMs, image generation models and voice models.
I tried but I only have 16g of ram and it wouldn’t complete a thought alas
Partially. I started with hosting my own llama3.2 + granite4 models using Ollama for my Home Assistant smart home and for general chat with OpenWebUI. I also run whisper for speech-to-text locally on my 1080 Ti GPU. I like the privacy and ownership of my self-hosted models, but I started to run into limitations with the small weights. So I built some tools that allow me to selectively route traffic to larger models hosted on DeepInfra depending on my need. For example, to GLM/Kimi models for code reviews or for my custom harnesses or harder problems.
I hosted Qwen 3.5 9b uncensored on my site at https://masland.tech/ for a while. I didn’t really use it and no one else used it so I took it down. These days I’m spending most of my time finding uses for AI and accessibility. One of the next things I’m planning is a video to text reasoning system, primarily for the purpose of grading used electronic devices.
