Re: Can anyone get Edge Copilot to work without logging in after July 2026?

Chris wrote:
> Maria Sophia <[email protected]> wrote:
>> Can anyone get Edge Copilot to work without logging in after July 2026?
>>   https://copilot.microsoft.com/
>> 
> 
> Just use a local model and don't bother with any of the online ones. They
> will *always* use you as training data unless you pay for a firewalled
> model. Doesn't matter whether you login or not.

Thanks for that idea, which, I agree, is the best way to run an LLM.

I researched the local models and they're perfect except... except that
they take a ton of disk space and seem to require a beefy machine.

Dunno if my 2009 Windows 10 desktop can handle a local model but I do agree
that's the way to go for someone like me who cares about privacy.

I'll have to look into it 'cuz these web-page LLMs have gotten me hooked on
the convenience, but, one by one, they've each started requiring a login. 

Looking it up, while other families exist (e.g., Qwen, DeepSeek, Gemma,
Mistral), apparently Llama remains the most widely used on Windows.

Disk space needed seems to be about 3-7 GB for an 8 billion parameters LLM
model, and maybe around 30-40 GB for a 70 billion parameters LLM model.

Parameters are the learned weights inside the neural network, where more
parameters add deeper reasoning and stronger language ability.	

Apparently disk space depends on quantization (i.e., compression) though.

Looking it up... 
The big problem is RAM where 64¡V128 GB RAM is normal for local LLMs.
The GPU needs to have VRAM starting at around 48 GB for local LLMs too.

Apparently nost consumer GPUs (RTX 3060/3070/3080/4070/4080) will not work
as we need workstation-class cards (i.e., RTX 6000 Ada, A100, H100, etc.).

To check a Windows box for those requirements, these commands help:
 wmic cpu get name
 wmic memorychip get capacity
 systeminfo | find "Total Physical Memory"
 wmic path win32_VideoController get name

In my case, my GPU has too little VRAM (2 GB) to run any modern model.
Worse, my CPU lacks AVX2, which slows down inference significantly.
Yet, my RAM (16 GB) is enough for small models but not medium or large.

My machine might be able to run 3B-4B models though. 
a. Phi-4 mini
b. Gemma 2 2B or 4B
c. Qwen 2.5 3B

That means my machine would likely only work with LM Studio or Ollama.
If I were to choose a setup for my old, 2009 Windows 10 box, it may be
 a. LM Studio GUI
 b. Phi 4 mini (3.8B) models
 c. Which should work with ~2-3 GB disk & 16 GB RAM 

For now, I don't have the time to research how to install a local LLM.
But if others are ahead of us, it would be good to know what they use.
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