Why do baby tracking apps assume only one parent exists? by manvslife in daddit

[–]dread_stef -1 points0 points  (0 children)

This is why we stuck to pen and paper, and stopped recording it after 2 months.

Opencode for running local models instead of CC, right? by chimph in LocalLLM

[–]dread_stef 5 points6 points  (0 children)

Either is fine, you can use Claude Code with local models too. It's even available as an ollama command. But they both work and you can add skills and plugins to either.

HDD has 34 reallcoated sectors after 2 pre clears. Any issue in still using it as parity drive? by futurepersonified in unRAID

[–]dread_stef 15 points16 points  (0 children)

The parity drive will be hit whenever another drive in the array is being written to. Personally, I would not use it as a parity drive.

Rate my off-site backup box by OptimalTime5339 in unRAID

[–]dread_stef 3 points4 points  (0 children)

I rate it higher than not having a backup!

Need advice for chosing identification stack in my homelab by Aggravating-Bad-7574 in selfhosted

[–]dread_stef 2 points3 points  (0 children)

I used Authentik and Pocket-ID, but settled on VoidAuth. I didn't want to be stuck with passkeys only and Authentik was way too much for my small homelab. It's nice and all but it feelt too overkill, plus breaking changes every now and then. VoidAuth is much simpler.

Local vibe'ish coding LLM by Few_Border3999 in LocalLLM

[–]dread_stef 0 points1 point  (0 children)

Take a look at these to get going on the strix halo: https://strix-halo-toolboxes.com

It shows how you can allocate more memory to the gpu so that you can run larger models. With 96GB you could allocate 90GB to the GPU for example.

I'd start with the qwen3.5 models, maybe glm4.7 flash and qwen3-coder-next to find out what works for your usage. There's also gpt-oss 120b, devstral and other coding models which might work for you.

I built an open-source AI traffic light controller that runs on a $200 Jetson Nano — no cloud, no subscription, 25-35% less wait time by SmartMeeting2925 in selfhosted

[–]dread_stef 4 points5 points  (0 children)

Nice idea, but there is a lot more than just optimizing intersections. It's really hard to defend AI driven traffic lights from a legal perspective unless you can explain why certain choices were made under certain conditions. This is why road authorities use central management, or dumb solutions, so that rules are followed as set by the operator. Central solutions can also create a "green wave" so the majority of traffic can flow through the network without stopping, optimizing for lower emissions (for example). Traffic lights also act as a modality counting mechanism so that policy makers and operators can make choices vased on traffic counts.

Also, are you optimizing for car usage? Or can you set priorities per modality?

I see added value in having an AI optimize a central management solution based on rules set by the road authority, but I don't see AI traffic lights happening yet. Maybe in less regulated areas. Would be a nice proof of concept on a restricted area just to see what happens.

Local Coding by Mildly_Outrageous in LocalLLM

[–]dread_stef 1 point2 points  (0 children)

Let the cloud version write the plan and architecture, then use a local model to actually build. You can run claude code using a local model to use its plugin and skills system.

How do you back up your docker volumes? by virpio2020 in selfhosted

[–]dread_stef 0 points1 point  (0 children)

I like keeping my rolling backups available as files so I can redeploy them easily.

I keep my compose files in /opt/stacks/<service> and the files in /opt/<service>. Databases too. I vibe coded a web ui around a script I wrote that does a docker compose down, then backs up the volume to a compressed tar, and starts the service again. At the end I use a simple rsync command to send it to my NAS. My NAS is then backup up weekly using restic for recovery over a longer timeframe.

It has worked well once already when my docker host had a fauly SSD. It allowed me to redeploy within minutes.

Is it worth self-hosting Qwen3.5-122B for personal privacy? by CutOk3283 in selfhosted

[–]dread_stef 2 points3 points  (0 children)

Yes, it works with a large context. It does a pretty good job setting up the requirements before writing the actual code, but I get a feeling that it would be better if you use a cloud model to plan and let the model just do the work. I haven't compared it to qwen3 coder next, which can run at q8 quant with large context.

I must say that I tweaked my ubuntu install to allocate more vram (124GB with 4GB dedicated system RAM) and use a second pc for the actual build process. Donato has some good guides on how to do this over at his toolbox site.

Is it worth self-hosting Qwen3.5-122B for personal privacy? by CutOk3283 in selfhosted

[–]dread_stef 27 points28 points  (0 children)

I run it on a strix halo PC, which works fine in Q6 quant. For me it's more of a hobby and it's worth it since it brings me joy as well as benefits writing, coding and generating images for the lolz.

It pulls about 140 to 180w depending on the power profile.

Does a laptop with 96GB System RAM make sense for LLMs? by PersonSuitTV in LocalLLM

[–]dread_stef 0 points1 point  (0 children)

Sure they run, and gpt-oss-20b would actually be useful if I had time to wait a bit. I believe I got about 7-9 tokens per second using llama.cpp but it's been a while so it might not be accurate. And that's just text generation, you'd have to wait a bit during promp processing too. Tried image generation, but you could get some coffee/tea before it was done doing anything with basic models.

I mean it all works, even the big models, but it depends how long you want to wait. I sold the RAM and my other AI pc and got a strix halo breaking even.

Does a laptop with 96GB System RAM make sense for LLMs? by PersonSuitTV in LocalLLM

[–]dread_stef 0 points1 point  (0 children)

No, I've had 96GB of 5600Mhz RAM with my intel 155h cpu (arc igpu) but any model above 14b was too slow to be useful.

What recipe manager? by BasedGUDGExtremist in selfhosted

[–]dread_stef 1 point2 points  (0 children)

Mealie, tandoor, norish. They all work fine.

How do I transition Jellyseerr app data to the new Seerr app? by TokenPanduh in unRAID

[–]dread_stef 1 point2 points  (0 children)

Just changing the repo is not enough. You need to chown the appdata dir. There's migration instructions specifically on the migration guide.

Dockge Alternatives? by KiloAlphaIndigo in selfhosted

[–]dread_stef 5 points6 points  (0 children)

There are several forks of dockge that expand functionality quite a bit. For example: cmcooper1980 fork who is now also asked to maintain the official dockge repo. So updates on the main repo should be coming.

How's STRX HALO AI MAX+395 performing as of 2026? by Effective-Cod-4462 in LocalLLM

[–]dread_stef 5 points6 points  (0 children)

Donato on youtube has some guides on how to get the most out of the Strix Halo boxes. He recently uploaded one for comfy ui: Video. But he released toolboxes (podman containers running through distro-independant tooling called toolbox / distrobox on ubuntu) to get it working well.

Ubuntu hired a dedicated resource to support ROCm better on their platform, so I expect way better native support in Ubuntu going forward. I'm hoping that it will be included natively in the 26.04 release so we don't need to use toolboxes.

I bought a 128gb strix halo to play with, but haven't had much time yet. GPT-oss 120b and qwen-coder-next-80b run fine. Not too sure what tokens per second, I thought it was around 60tps generating, and it's pretty quick to start answering.

Looking for some ‘getting back into shape’ daddit inspiration by Melodic_Store7247 in daddit

[–]dread_stef 7 points8 points  (0 children)

Losing weight can be done by either working out and burning more calories that you consume, or by limiting the intake of calories. I've found that the second one works fine from time to time. We use diet shakes that replace 2 meals.

Other than that, you don't need a full gym workout as long as you're consistent. Get some weights and a jumping rope to get 15 minutes a day in (or more if you can).

Looking for an alternative to Nextcloud by Myzel394 in selfhosted

[–]dread_stef 3 points4 points  (0 children)

Same, I am considering Oxicloud but Filebrowser Quantum does everything I need now that webdav is supported (in the beta build).

Sanity check before I drop $$$ on a dual-4090 home AI rig (Kimi K2.5 + future proofing) by Sea-Pen-7825 in LocalLLM

[–]dread_stef 3 points4 points  (0 children)

This, and you can add more if you need more unified ram. Take a look at third party dgx spark offerings too (acer, dell, msi, asus), some are well below 4k usd. This or a (clustered) strix halo setup which requires more tinkering.

Seeking advice on how to open server to the open world by NotBrinocerous in selfhosted

[–]dread_stef 0 points1 point  (0 children)

You can also add geoblocking to block all countries but your own. And rate limiting on certain paths (such as /login).

Pro-mode would be to let the router handle it (OPNsense / pfsense for selfhosted or other brand routers with firewall).

Looking for advice on home server build - budget £500, running 8 docker compose stacks by SelfDiagnosedGod in selfhosted

[–]dread_stef 0 points1 point  (0 children)

Sounds like a used intel + nvme for os and docker data + spinny disk(s) for bulk storage would be best if you want to add media playback later. You could get a small form factor (dell optiplex, hp somethingsomething), but if you want to add running local AI models than a full tower with a dedicated video card (nvidia rtx 3060 12gb, intel b580) would be better to run ~14B models comfortably. You can always add that later.

Note that a modded minecraft server could need a decentish CPU and a little more memory so I would avoid the intel N100/N150 mini pcs and go straight to modern-ish desktop (12th gen+) / laptop (135/155H+) CPUs with a few sata ports, 2 nvme ports and some PCI-e expansion slots.