alt Hacker NewsCan I run AI locally?
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This just reminded me of this https://www.systemrequirementslab.com/cyri.
Not sure if it still works.
Missing the A18 Neo! :)
For me the "can run" filter says "S/A/B" but lists S, A, B, and C and the "tight fit" filter says "C/D" but lists F.
Just FYI.
Finally! I've been waiting for something like this.
For image generation or even video generation, local models are totally feasible. I can generate a 5 second clip with wan 2.2 in about 30 minutes on my 3060 12G. Plus, I have full control on the loras used.
Cool website. The one that I'd really like to see there is the RTX 6000 Pro Blackwell 96 GB, though.
What is this S/A/B/C/etc. ranking? Is anyone else using it?
Missing laptop versions of all these chips.
Is there a reliable guide somewhere to setting up local AI for coding (please don’t say ‘just Google it’ - that just results in a morass of AI slop/SEO pages with out of date, non-self-consistent, incorrect or impossible instructions).
I’d like to be able to use a local model (which one?) to power Copilot in vscode, and run coding agent(s) (not general purpose OpenClaw-like agents) on my M2 MacBook. I know it’ll be slow.
I suspect this is actually fairly easy to set up - if you know how.
Why isn't there some kind of benchmark score in the list?
Missing RTX A4000 20GB from the GPU list.
Oh how cool. Always wanted to have a tool like this.
Missing 5060 Ti 16GB
If anyone hasn't tried Qwen3.5 on Apple Silicon, I highly suggest you to! Claude level performance on local hardware. If the Qwen team didn't get fired, I would be bullish on Local LLM.
What is S? Also, NVIDIA RTX 4500 Ada is missing.
Does it make any sense? I tried few models at 128GB and it's all pretty much rubbish. Yes they do give coherent answers, sometimes they are even correct, but most of the time it is just plain wrong. I find it massive waste of time.
could you add raspi to the list to see which ridiculously small models it can run?
Hugging Face can already do this for you (with much more up-to-date list of available models). Also LM Studio. However they don't attempt to estimate tok/sec, so that's a cool feature. However I don't really trust those numbers that much because it is not incorporating information about the CPU, etc. True GPU offload isn't often possible on consumer PC hardware. Also there are different quants available that make a big difference.
On mobile it does not show the name of the model in favor of the other stats.
This does not seem accurate based on my recently received M5 Max 128GB MBP. I think there's some estimates/guesswork involved, and it's also discounting that you can move the memory divider on Unified Memory devices like Apple Silicon and AMD AI Max 395+.
awesome, needed this
My Mac mini rocks qwen2.5 14b at a lightning fast 11/tokens a second. Which is actually good enough for the long term data processing I make it spend all day doing. It doesn’t lock up the machine or prevent its primary purpose as webserver from being fulfilled.
1. More title attributes please ("S 16 A 7 B 7 C 0 D 4 F 34", huh?)
2. Add a 150% size bonus to your site.
Otherwise, cool site, bookmarked.
Nice UI, but crap data, probably llm generated.
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if you do, would you still want to collect data in a single pane of glass? see my open source repo for aggregating harness data from multiple machine learning model harnesses & models into a single place to discover what you are working on & spending time & money. there is plans for a scrobble feature like last.fm but for agent research & code development & execution.
https://github.com/russellballestrini/unfirehose-nextjs-logg...
thanks, I'll check for comments, feel free to fork but if you want to contribute you'll have to find me off of github, I develop privately on my own self hosted gitlab server. good luck & God bless.
Has anyone actually built anything with this tool?
The website says that code export is not working yet.
That’s a very strange way to advertise yourself.