Selfhosted

63012 readers

1651 users here now

A place to share alternatives to popular online services that can be self-hosted without giving up privacy or locking you into a service you don't control.

Rules:

Detailed Rules Post

Be civil.
No spam.
Posts are to be related to self-hosting.
Don't duplicate the full text of your blog or readme if you're providing a link.
Submission headline should match the article title.
No trolling.
Promotion posts require active participation, with an account that is at least 30 days old. F/LOSS without a paywall has exceptions, with requirements. See the rules link for details. Tags [CBH] or [AIP] are required, see the links in Rule 8 for details.
AI-related discussions and AI-involved promotional posts have additional requirements for tagging, as noted in Rule 7 and the AI & Promotional Post Expanded Rules post, and find example disclosures here.

Resources:

selfh.st Newsletter and index of selfhosted software and apps
awesome-selfhosted software
awesome-sysadmin resources
Self-Hosted Podcast from Jupiter Broadcasting

Any issues on the community? Report it using the report flag.

Questions? DM the mods!

founded 3 years ago

MODERATORS

curbstickle@anarchist.nexus

curbstickle_lw@lemmy.world

Is anyone self-hosting their own AI? (lemmy.zip)

submitted 18 hours ago by StateMachine@lemmy.zip to c/selfhosted@lemmy.world

128 comments fedilink hide all child comments

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.

you are viewing a single comment's thread
view the rest of the comments

[–] miaowoo_lw@lemmy.world 3 points 1 hour ago

Not OP but running local LLMs for exactly the privacy reasons you describe, some practical notes:

For a no-GPU start: llama.cpp (or Ollama as a wrapper) with Qwen3-4B/8B or Llama-3.1-8B at Q4_K_M runs fine on a plain x86 box with 16GB RAM. Speed on CPU is ~5-15 tok/s for 4B-class models, which is usable for search summarization and drafting, painful for long chats.
Quantization is the whole game: 8B Q4 is ~5GB and close to fp16 quality for everyday tasks; don't run fp16 on consumer hardware, run the bigger model more quantized instead.
For your "web search without profiling" use case the actual stack that matters is: SearXNG (self-hosted metasearch, no tracking) -> fetch top N pages -> feed text to the local model for summarization. The LLM part is almost the trivial bit; the search layer is what fixes the privacy problem.
Remote access: don't expose Ollama/Open WebUI directly. WireGuard (or Tailscale if you don't want to manage keys) and you get it on the phone with zero ports open.
One honest caveat: local small models are noticeably worse at factual recall than cloud ones. Where they shine is processing text you hand them (summaries, extraction, rewriting). Design your workflows around that and the gap mostly disappears.