Local LLMs are the way to go on AI, they can’t suddenly change the model up on you. And also, I guess Anthropic just wants their models to be more useless ahead of going public? Because I presume people that want to use AI, who don’t care where they send their data to, but don’t want to nagged about how they can’t do benign programming and analysis tasks, will just choose another model provider.
They are the way to go, but hardware pricing makes it cost-prohibitive to match frontier capabilities, which makes decomp and recomp difficult. Or rather, they require more skill and take longer, introducing some barriers against the current floodgates being flung open.
We all know the eye-watering prices GPUs and RAM cost now, to say nothing of Unified Memory devices like the Strix. Most people just don’t have a spare $10K to throw at an inference box that can run (say) a 300B model at interactive (not batch) speeds.
Coming at this from another angle tho, I note that according to Steam stats, the most popular consumer GPUs are in the 8GB and 16GB range…which is smack bang in the VRAM range of what a good MoE (say, Qwen 3.6 35B-A3B) runs on (for 8GB) or arguably the best local dense coder (Qwen 3.8 27B) can live at. Which leaves us with a capable assistant and a capable coder.
I think there’s probably room for LLM improvement in the 8–16GB range too…and given that most consumer PCs and laptops live there, I’m sanguine the open-weight devs might make it happen.
But I also suspect the gatekeeping of high-end capacities is intentional.
We’re probably not going to have the ability to vibe code Mario into Elden Ring again…not without significantly more skill. Dunno.
It’s more about not spooking investors. If it’s known that your AI is being used to reverse engineer software from well off corporations. They’re going to be a little less likely to invest if 1: They’re connected to any of those corporations 2: They’re concerned about future lawsuits heading their way.
And of course the actual fear of potential lawsuits landing on their door, or being named in lawsuits against people using their AI to do this.
Yes, if you want control over AI you MUST host it yourself in reality.
I still can’t wrap my head around how this strategy (“buy our models, they are so powerful they might kill all humans”) would work in their favor, apart from one thing: restrictions would hurt Chinese models probably more than themselves. But I find it very unlikely that characters like Altman or Amodei would be capable of playing that kind of 4d chess. It’s a weird flex
No, but if you were an investor, would you invest in a product that would make it so people can easiy recreate your other products so that they stop buying your other products? Ending humanity doesn’t scare them but making $0.75 less this year does
In the US code is copyrighted the same as literary works. But that only covers the actual lines of code and not the ideas, functions or algorithms they implement. This means that if someone copy pastes your code word for word they are infringing your copyright but if they write their own code that does the same function as yours they are fine.
Human-generated code absolutely is, correct. But AI-generated code is still untested. AI-generated art does not have copyright protection currently. My money is that AI-generated code will have copyright protection through some mental and legal gymnastics. Because money.
Copyright generally requires human expression regardless of what the type of work is, it’s not about what you were inspired by
If you did derive your work from something else and yours is similar enough, then now both you and the original author has separate copyrights on the result which both needs to be licensed to sell the work (prime example is book translations)
Oh, AI-generated code may not be, but like you said we don’t have a court ruling yet.
I don’t think it can’t be, but we’d first have to have models trained without violating the rights of all the authors of the works in the training data. Like if you trained a model only on GPL software, then the model and its output should also be GPL.
but we’d first have to have models trained without violating the rights of all the authors of the works in the training data. Like if you trained a model only on GPL software, then the model and its output should also be GPL.
I’m not so convinced on that one. Copying code without permission, yes, that’s illegal. Distributing copied code without permission, also illegal. But processing code (copied with permission) into weights, that doesn’t feel to me like a violation. If I have a legit copy of something, I should be able to distribute computed statistics about that copy.
These corporations give these ai companies their data too. Many of them pretend to protect sensative data but we all know that’s not true.
So it certainly doesn’t make you look trust worthy when you ask a company to hook your ai up to their entire data base, then suddenly a million little clones are made by individuals using the same ai program you run.
This is where they’re gonna make things less secure as far as national security - foreign local models won’t have these restrictions for obvious reasons, so people will gladly install those and ignore crippled domestic options.
Uhm yeah good luck with running anything locally after hardware prices double again and again. Big tech needs to be stopped. There is no wiggling out of this just by being a smart customer.
The price did grow several times in size, but even in the 4 to 5 digit price range, you or smaller companies can have a pretty competitive performing open source model as the frontier models from earlier this year and they are keeping pace.
Obviously I’d like the speculation bubble to end and the DRAM and GPU cartels broken up, as it’s late-stage capitalism where the existing regulations being unenforced on big tech because the regulators are in on it that’s the problem, not so much the AI tech itself. (Don’t get me wrong, the tech has bad sides to it too like stealing artwork, data centre environmental impact and whatnot, but just speaking to the cause of the component greedflation).
Yes it’s disgustingly expensive. I spent a whole lot of money on an old used GPU and it felt bad, but it didn’t feel dirty like paying for Claude would. And then a couple of weeks later the used prices for this GPU had risen by about 15%.
(I only use Claude at work when someone else is paying. And they’re about to make me redundant because Claude is cheaper than me.)
Another good option is Qwen3.5-9B. I’d try a Q4 or Q5.
Whichever model you choose, I’d also suggest a few MCP servers to give it access to reliable information rather than rely entirely on its internal knowledge.
Microsoft Learn MCP: Official PowerShell, Windows and network documentation. Will help with your scripting stuff.
I’d start with Microsoft Learn and Exa, then add the others as needed. You’ll need an MCP-capable client (which pretty much all of them are now - eg: llama.cpp web ui, OpenWebUI, Light Local Chat etc), and I’d keep file access read-only initially.
I’d personally use McProxy instead of adding MCPs singularly, but I fear I’m already over loading you with information.
EDIT: The PolyStrata recommendation assumes you have a discrete GPU with sufficient VRAM (unclear if you do?). If not, disregard Ornith and try Tiny Ling 3 Q6 or Qwen3.5-9B with ik_llama.cpp instead.
Either way, both smaller models should be capable of the tasks you’ve described, particularly with access to the right documentation. Just verify any network or firewall changes before applying them.
With an iGPU results are going to be very slow. Most promising things I have heard of so far is Mixture of Experts type models, if you have an 8GB card you might be able to run Qwen 3.8-35B-A3B-MoE which I think is the most capable for that hardware.
There are websites that can suggest a few for your specific hardware, I assume some are vibecoded and are only occasionally updated to the latest models, so take it as you will. See this Lemming’s comment. And [email protected] is where I think most of the discussion around new development with Local LLMs happens here on Lemmy.
Local LLMs are the way to go on AI, they can’t suddenly change the model up on you. And also, I guess Anthropic just wants their models to be more useless ahead of going public? Because I presume people that want to use AI, who don’t care where they send their data to, but don’t want to nagged about how they can’t do benign programming and analysis tasks, will just choose another model provider.
They are the way to go, but hardware pricing makes it cost-prohibitive to match frontier capabilities, which makes decomp and recomp difficult. Or rather, they require more skill and take longer, introducing some barriers against the current floodgates being flung open.
We all know the eye-watering prices GPUs and RAM cost now, to say nothing of Unified Memory devices like the Strix. Most people just don’t have a spare $10K to throw at an inference box that can run (say) a 300B model at interactive (not batch) speeds.
Coming at this from another angle tho, I note that according to Steam stats, the most popular consumer GPUs are in the 8GB and 16GB range…which is smack bang in the VRAM range of what a good MoE (say, Qwen 3.6 35B-A3B) runs on (for 8GB) or arguably the best local dense coder (Qwen 3.8 27B) can live at. Which leaves us with a capable assistant and a capable coder.
I think there’s probably room for LLM improvement in the 8–16GB range too…and given that most consumer PCs and laptops live there, I’m sanguine the open-weight devs might make it happen.
But I also suspect the gatekeeping of high-end capacities is intentional.
We’re probably not going to have the ability to vibe code Mario into Elden Ring again…not without significantly more skill. Dunno.
It’s more about not spooking investors. If it’s known that your AI is being used to reverse engineer software from well off corporations. They’re going to be a little less likely to invest if 1: They’re connected to any of those corporations 2: They’re concerned about future lawsuits heading their way.
And of course the actual fear of potential lawsuits landing on their door, or being named in lawsuits against people using their AI to do this.
Yes, if you want control over AI you MUST host it yourself in reality.
Why? Reverse engineering is neither unethical or illegal.
I never said it was. But, I’m also not an investor. I’m just saying the kind of things that scare off investors. And this would be a big one.
What? The literal extermination of the human race is not enough to scare off investors.
Have you seen the investment in fossil fuels. 😄
🤣😂🥲🙂😐😔🥺😭
Killing the entire species is absolutely less of a concern for investors than copyright violations.
At this point, I think they believe it’s a good indicator of potential. A way of saying just how awesome and magical and powerful the AI is.
Otherwise the “AI went off the rails and breached X companies servers” would also have been met with contempt and negatively impacted them.
I still can’t wrap my head around how this strategy (“buy our models, they are so powerful they might kill all humans”) would work in their favor, apart from one thing: restrictions would hurt Chinese models probably more than themselves. But I find it very unlikely that characters like Altman or Amodei would be capable of playing that kind of 4d chess. It’s a weird flex
No, but if you were an investor, would you invest in a product that would make it so people can easiy recreate your other products so that they stop buying your other products? Ending humanity doesn’t scare them but making $0.75 less this year does
Well, to be blunt, it depends. Would the eventual extermination of the human race cause them to lose money in the short term?
It’s dangerous for IP, though.
Only if it is protected.Which code is afaik not.
In the US code is copyrighted the same as literary works. But that only covers the actual lines of code and not the ideas, functions or algorithms they implement. This means that if someone copy pastes your code word for word they are infringing your copyright but if they write their own code that does the same function as yours they are fine.
It absolutely is.
Human-generated code absolutely is, correct. But AI-generated code is still untested. AI-generated art does not have copyright protection currently. My money is that AI-generated code will have copyright protection through some mental and legal gymnastics. Because money.
Copyright generally requires human expression regardless of what the type of work is, it’s not about what you were inspired by
If you did derive your work from something else and yours is similar enough, then now both you and the original author has separate copyrights on the result which both needs to be licensed to sell the work (prime example is book translations)
Oh, AI-generated code may not be, but like you said we don’t have a court ruling yet.
I don’t think it can’t be, but we’d first have to have models trained without violating the rights of all the authors of the works in the training data. Like if you trained a model only on GPL software, then the model and its output should also be GPL.
I’m not so convinced on that one. Copying code without permission, yes, that’s illegal. Distributing copied code without permission, also illegal. But processing code (copied with permission) into weights, that doesn’t feel to me like a violation. If I have a legit copy of something, I should be able to distribute computed statistics about that copy.
EFF points out some hazards: https://www.eff.org/deeplinks/2026/10/rewriting-copyright-law-generative-ai-would-hurt-everyone
These corporations give these ai companies their data too. Many of them pretend to protect sensative data but we all know that’s not true.
So it certainly doesn’t make you look trust worthy when you ask a company to hook your ai up to their entire data base, then suddenly a million little clones are made by individuals using the same ai program you run.
If investors aren’t spooked already, they’re mentally deficient anyway.
This is where they’re gonna make things less secure as far as national security - foreign local models won’t have these restrictions for obvious reasons, so people will gladly install those and ignore crippled domestic options.
Yes we must support our domestic Cambodian models!
Uhm yeah good luck with running anything locally after hardware prices double again and again. Big tech needs to be stopped. There is no wiggling out of this just by being a smart customer.
Thing is, I already am…
The price did grow several times in size, but even in the 4 to 5 digit price range, you or smaller companies can have a pretty competitive performing open source model as the frontier models from earlier this year and they are keeping pace.
Obviously I’d like the speculation bubble to end and the DRAM and GPU cartels broken up, as it’s late-stage capitalism where the existing regulations being unenforced on big tech because the regulators are in on it that’s the problem, not so much the AI tech itself. (Don’t get me wrong, the tech has bad sides to it too like stealing artwork, data centre environmental impact and whatnot, but just speaking to the cause of the component greedflation).
Yes it’s disgustingly expensive. I spent a whole lot of money on an old used GPU and it felt bad, but it didn’t feel dirty like paying for Claude would. And then a couple of weeks later the used prices for this GPU had risen by about 15%.
(I only use Claude at work when someone else is paying. And they’re about to make me redundant because Claude is cheaper than me.)
Is there a local LLM I can run on an 8-10th gen i5 with 16GB RAM?
Yes, quite a few, but it depends on what you’re trying to do with them. Any ideas?
Assist with writing letters, home assistant code, light powrshell scripting.
Edit: helping segment my network
That should be well within reach of a local LLM.
If you’ve got a discrete GPU with sufficient VRAM, something like Ornith running on PolyStrata could be worth a shot. Try a Q3 size.
https://huggingface.co/bartowski/Ornith-1.5-35B-A3B-GGUF
https://github.com/VecSzn/PolyStrata
Hell, Tiny Ling 3 might be able to do it. Try a Q6.
https://huggingface.co/bartowski/Ling-3.0-tiny-GGUF
Another good option is Qwen3.5-9B. I’d try a Q4 or Q5.
Whichever model you choose, I’d also suggest a few MCP servers to give it access to reliable information rather than rely entirely on its internal knowledge.
https://learn.microsoft.com/en-us/training/support/mcp
https://github.com/exa-labs/exa-mcp-server
https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem
If you’re actually running Home Assistant, its official MCP server is worth a look too.
https://www.home-assistant.io/integrations/mcp_server/
I’d start with Microsoft Learn and Exa, then add the others as needed. You’ll need an MCP-capable client (which pretty much all of them are now - eg: llama.cpp web ui, OpenWebUI, Light Local Chat etc), and I’d keep file access read-only initially.
I’d personally use McProxy instead of adding MCPs singularly, but I fear I’m already over loading you with information.
EDIT: The PolyStrata recommendation assumes you have a discrete GPU with sufficient VRAM (unclear if you do?). If not, disregard Ornith and try Tiny Ling 3 Q6 or Qwen3.5-9B with ik_llama.cpp instead.
https://github.com/ikawrakow/ik_llama.cpp
Either way, both smaller models should be capable of the tasks you’ve described, particularly with access to the right documentation. Just verify any network or firewall changes before applying them.
With an iGPU results are going to be very slow. Most promising things I have heard of so far is Mixture of Experts type models, if you have an 8GB card you might be able to run Qwen 3.8-35B-A3B-MoE which I think is the most capable for that hardware.
There are websites that can suggest a few for your specific hardware, I assume some are vibecoded and are only occasionally updated to the latest models, so take it as you will. See this Lemming’s comment. And [email protected] is where I think most of the discussion around new development with Local LLMs happens here on Lemmy.
links
They suck far too much at the moment.