I added one tool to my local LLM setup, and it finally stopped making things up
… What happened here is that the model knew it had access to the tool, but didn’t know how to use it cleanly. …
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I connected my local LLM to my browser and it changed how I automated tasks
… Since everything runs locally, responses are fast and there’s no friction of logging in, hitting limits, or worrying about sending sensitive data outside. There’s another obvious benefit to connecting a local LLM to a browser — you can use AI for your queries and have your data private. …
Stop obsessing over your GPU's core clock — memory clock matters more for local LLM inference
… LLMs force your GPU to spend most of the time moving data in and out of the VRAM. They repeatedly access large matrices and key-value cache KV cache , which require high-bandwidth memory for efficient storage. …
After a year of self-hosting LLMs, I realized the real bottleneck isn’t the GPU
… You can have the fastest, smartest model in the world, but if it doesn’t have access to your actual data, it’s like a genius locked in a dark room. …
Your old GPU can still run big LLMs – you just need the right tweaks
… Sign in to your XDA account Running large language models on local hardware not only lets you avoid paying monthly subscriptions to cloud providers, but also prevents large corporations from gaining access to your private data. …
Local AI isn't just Ollama—here's the ecosystem that actually makes it useful
… Only then was I able to feel the power of having an LLM on my local system, with no limits, no fees, and no data sitting on third-party servers. …
TurboQuant tackles the hidden memory problem that's been limiting your local LLMs
… The rotation makes the data statistically uniform based on the vector's dimension alone, not the actual data. Because the distribution is known in advance, optimal compression codebooks can be precomputed and reused everywhere, without the need for per-block metadata. …
I automated my entire read-it-later workflow with a local LLM so every article I save gets summarized overnight
… You could technically use something like ChatGPT or Claude , but it'd require access to their API, which costs money. Keeping things local ensures that none of your data touches a third-party server, and there's not much advantage to using a big name LLM for simple summarization tasks. …