I stopped trying to replace my cloud LLMs, and local models finally made sense
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Speculative decoding made my local LLM actually usable
…Sign in to your XDA account Local LLMs have this annoying middle ground problem. They're good enough that you can see the potential, but just slow enough to get in the…
I thought I needed a GPU for local LLMs until I tried this lean model
…Sign in to your XDA account When it comes to local LLMs, we have been told that if you aren’t packing a high-end GPU with a massive pool of VRAM…
Your local LLM feels weak because you're treating it like a search engine
…Sign in to your XDA account I’ve been running my local LLM for a while now, and it’s been hit and miss for me. For starters, I do kind of…
Local LLMs perform so much better when you teach them to ask before they answer
…Sign in to your XDA account Prompting an LLM requires a different approach than typing a search query into Google, yet it's common for people to treat them the same . The…
I added one tool to my local LLM setup, and it finally stopped making things up
…Sign in to your XDA account Local LLMs have been gaining traction these past couple of years, and I wanted to see what it's like building a small, self-contained setup…
I replaced NotebookLM with this free tool that uses my local LLMs
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Two old GPUs I salvaged are doing more AI work than a brand new $2000 card, and I won't be upgrading anytime soon
…Sign in to your XDA account Despite the productivity-oriented perks of large language models, there’s the misconception that local LLMs need a lot of computational horsepower to run. Well, it…
Trying to self-host LLMs made me realize local AI has a friction problem, not a quality problem
…Sign in to your XDA account Summary Local LLMs have swiftly improved and can rival cloud models on capable hardware. Setup, research, and driver headaches make local AI feel niche and frustrating…
I replaced cloud LLMs with local models running off a Proxmox LXC, and the performance trade-off was worth it
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