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15 hours agoYep, I think we have the winner. I’ve just installed it today and I’m actually responding to your post using handy right now. It’s a really great piece of software. Thank you to both of you that recommended this.
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Cake day: May 14th, 2026
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Bemused I guess? At least Anthropic made theirs funny
openwhispr
Second time today that has come up - I better go look. Cheers!
Thank you!
Thanks - that’s worth a gander
Thank you!
Thank you!
Awesome!
Aussie too - same issue with having to fake accent sometimes :)
Quite a lot, actually.
Coding, document analysis, STT, home assistant, shopping assistant, gaming, journalling, image and video generation, OCR, language translation, recipe/meal / workout planning, study/flashcard generation, email drafting, adversarial review, search engine on steroids, hardware troubleshooter, companion for elder care, music curator and DJ …
All of that without creepy ass cloud shit from Big AI.
I can go on, but “a lot” probably covers it.
EDIT: asked, answered and…down voted. Classic Lemmy anti-ai knee jerk. FWIW I work with AI in healthcare settings as well as code review for my own personal projects.
What I said are actual use cases, not a wishlist generated by Jippity. I can elaborate on any and all of them with actual real life experience.
I’m confused. Are futo the bad guys now? All I know about them is that Louis Rossman used to be involved with them. I like Rossman’s stuff / the futo speech to text is great (gladly donated to it).
Dunno if Rossman’s split with them was just so he could focus on FULU or something more.
Hmm…it runs on a 1060…it’s a MoE not a dense. 24B is even lighter. Worth a shot.
https://www.youtube.com/watch?v=8F_5pdcD3HY
Else, if youre looking for a coding model (??) something like Sara or fara might suit
I mean…that entirely depends on your use case - and I hate saying that. For me and what I do, Qwen SLM (esp Qwen3-4B 2507 instruct and Qwen3.5-2B) are exceptional. But I’m not trying to do Claude at home.
Best bet? Spend $10 on OpenRouter and try different models. In a head to head with ChatGPT 5.4 mini (excellent for coding BTW), I’ve found Qwen 3.5 27B more than able to hold its own for coding tasks…IF you narrowly gate it/confine it. The last batch of Qwen’s really are something. Dunno about the 3.7 series.
Having said ALL that, I’m really tempted to go back in time and code myself a deterministic expert system, with user updatable knowledge cascade, tool calling and a minimal amount of Markov chain word garnish for flavour. I think we use to just call that “a program” lol.
Really tempted actually, because if 50% of llm use case is basically Super Google but not shit…well, I can make that myself. I just need to point my autism at it.
PS: this might help
Numbers about 3-4x. The P100 is near 800 GB/s. The 1080 is what… 192GB/s? Hell, even if it were double that, HBM2 simply has larger bandwidth. The 1080 was a gaming card; the P100 is a server / number cruncher.
Just for sake of completion
Pros
Mature project (around since the early 2000s)
Lightweight compared to Immich
Designed as a photo library first, not an AI platform
Albums, tags, metadata, permissions
Huge plugin ecosystem
Runs happily on modest hardware
Can manage very large collections
Doesn’t demand phone-app-centric workflows (though of course it has a phone to computer app / sync)
Cons
Feels more like a traditional photo archive than Google Photos
Mobile experience is functional rather than slick
No fancy AI search or face recognition by default (though can add easy enough)
UI is a bit “classic web”
Huh - cheaper than the P40s (though less VRAM) but larger bandwidth due to HBM2. Good looking out
You probably could. A Tesla P4 or P40 (old data centre cards) are more than up to the job. My Lenovo tiny hosts a P4 (card cost $100 on eBay; the lenovo itself was $200ish) and runs Qwen3.5-35B-A3B at about 20 tok/s. Smaller models are even faster.
https://www.youtube.com/watch?v=8F_5pdcD3HY
If you’re not bound by the one liter shoebox design, then the P40 is still a great and inexpensive card.
I think I mentioned elsewhere but right now I’m trying to figure out if I can use a magic packet from the Raspberry Pi to wake up the Lenovo as needed rather than leaving it on all the time.
Agree. I know the Pi’s are out of favour these days…but they are a cool little machine. I got mine running DietPi and a bunch o crap (the usuals - JF, arr stack, pi hole, syncthing, yadda yadda) and running headless the footprint (power and memory wise) is tiny.
I joked about the 4xAA batteries thing but iirc, there is actually a Pi-HAT that creates a micro UPS that’ll run the pi for maybe three to five hours just on double A batteries.
Edit: yep
https://pimodules.com/product/ups-pico-hv4-0-advanced
or more sensibly
There’s an argument to be had regarding a MoE versus a small dense model. I guess it depends on what exactly you need doing with it. I would be tempted to run a smaller dense model (like a Qwen 3-14B or a Qwen 3.5 9B) as at a reasonable quant, it might fit mostly or entirely on the GPU, thereby giving you excellent speeds.
PS: I’m actually in the process of designing an expert system (not a LLM) for pretty much the task you described. The intention is that you would still interact with it like a large language model, but the actual brains underneath it would be something more traditional.
For $10, that’s quite impressive. I’m familiar with several of those games, including Just Cause 2, which I have run on i5-4785t (iGPU only) at 630p, hitting 69fps (albeit it AA off etc, AF 4x, textures high, shadows low, medium water and object details etc).
OTOH, the i5-4785T doesn’t hit 90+ degrees to do it :) (sits around 70) and sips ~40W.
EDIT: from the video, the test rig was -
Test Bench Specs: • CPU: Intel Core 2 Duo E7500 @ 3.8GHz OC • RAM: 8GB DDR2 • GPU: ATI Radeon HD 3850 512MB • Storage: 1TB SATA SSD • PSU: 450W 80+ Bronze • OS: Windows 7 x64