1. Use Tor to access the provider?
2. Create a random account?
3. Use some form of untraceable payment (which one?)
4. Scrub all information provided to the LLM from personally identifiable information?
It seems like a lot of effort. So is running a local LLM, for which I don't even have the hardware. How do you do it?Ask HN: How do you use LLMs for private discussions?
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Re: Ask HN: How do you use LLMs for private discussions?
#2Re: Ask HN: How do you use LLMs for private discussions?
#3Re: Ask HN: How do you use LLMs for private discussions?
#4I spin up a gpu instance in a cloud, run my model via vllm, connect to it via an ssh tunnel. done.
Re: Ask HN: How do you use LLMs for private discussions?
#5I spin up a gpu instance in a cloud, run my model via vllm, connect to it via an ssh tunnel. done.
Can you elaborate on the first step? Which cloud and which service? What's the cost outlay if you are just having a convo and not doing anything 'agentic'?
It depends, but usually spin up an h100 on lambda.ai or coreweave. They have capacity and their UIs/APIs are nice. I spin it up for an hour or two, believe it was 6~ dollars an hour.
Once the gpu instance is up, you need to run vllm and a model, ie https://docs.lambda.ai/education/large-language-models/deplo....
Then you can connect your pi.dev, openwebui, etc etc to vllm and interact with it like normal.
Re: Ask HN: How do you use LLMs for private discussions?
#6Re: Ask HN: How do you use LLMs for private discussions?
#7Re: Ask HN: How do you use LLMs for private discussions?
#8The models I'm using right now with that are:
gpt-oss-120b-F16.gguf
Qwen_Qwen3.5-27B-Q4_K_M.gguf
Qwen3.6-35B-A3B-UD-Q5_K_XL.gguf
gemma-4-31B-it-UD-Q6_K_XL.gguf