<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Llama Builds</title><description>Independent buying guides, benchmarks, and PC builds for running LLMs locally. Find the right GPU for the models you want to run, and the models your GPU can run.</description><link>https://llamabuilds.ai/</link><language>en-us</language><item><title>The best GPUs for running AI models locally (2026)</title><link>https://llamabuilds.ai/best/gpus-for-local-llms/</link><guid isPermaLink="true">https://llamabuilds.ai/best/gpus-for-local-llms/</guid><description>The best GPUs for running LLMs at home in 2026, chosen on VRAM, memory bandwidth and October 2026 prices, with estimated speeds on current open models.</description><pubDate>Wed, 14 Oct 2026 00:00:00 GMT</pubDate><category>buying-guide</category><category>gpus</category><category>buying guide</category><category>vram</category><category>nvidia</category><category>amd</category><category>intel</category></item><item><title>How much VRAM do you need to run LLMs locally?</title><link>https://llamabuilds.ai/guides/how-much-vram-do-you-need/</link><guid isPermaLink="true">https://llamabuilds.ai/guides/how-much-vram-do-you-need/</guid><description>Plan on about 0.6GB of VRAM per billion parameters at Q4_K_M, plus context and overhead. Tables by model size, quantization, context length and GPU tier.</description><pubDate>Wed, 14 Oct 2026 00:00:00 GMT</pubDate><category>explainer</category><category>vram</category><category>hardware</category><category>kv-cache</category><category>quantization</category><category>beginners</category></item><item><title>LLM quantization explained: what Q4_K_M, Q8_0 and the rest mean</title><link>https://llamabuilds.ai/guides/llm-quantization-explained/</link><guid isPermaLink="true">https://llamabuilds.ai/guides/llm-quantization-explained/</guid><description>What GGUF quant names like Q4_K_M and Q8_0 mean, how much quality each level loses in published benchmarks, and how to pick one for your VRAM.</description><pubDate>Wed, 14 Oct 2026 00:00:00 GMT</pubDate><category>explainer</category><category>quantization</category><category>gguf</category><category>llama-cpp</category><category>mlx</category><category>beginners</category></item><item><title>The best Macs and mini PCs for running LLMs locally (2026)</title><link>https://llamabuilds.ai/best/macs-and-mini-pcs-for-local-llms/</link><guid isPermaLink="true">https://llamabuilds.ai/best/macs-and-mini-pcs-for-local-llms/</guid><description>Our 2026 picks among Mac Studio, DGX Spark and Ryzen AI Max+ mini PCs for running big LLMs on unified memory, with usable GPU memory, estimated speeds and prices.</description><pubDate>Wed, 14 Oct 2026 00:00:00 GMT</pubDate><category>buying-guide</category><category>mac</category><category>mini pc</category><category>unified memory</category><category>apple silicon</category><category>strix halo</category><category>dgx spark</category><category>buying guide</category></item><item><title>NVIDIA GPUs on Linux for local AI: which cards to buy and how to set them up</title><link>https://llamabuilds.ai/guides/nvidia-gpus-on-linux/</link><guid isPermaLink="true">https://llamabuilds.ai/guides/nvidia-gpus-on-linux/</guid><description>Which NVIDIA cards behave on Linux for 24/7 AI work, why fan control and cooling matter, and how to set up drivers, CUDA, llama.cpp and Ollama on Ubuntu.</description><pubDate>Thu, 14 Aug 2025 00:00:00 GMT</pubDate><category>how-to</category><category>linux</category><category>ubuntu</category><category>nvidia</category><category>drivers</category><category>cuda</category><category>setup</category></item><item><title>Is the RTX 3090 still the best GPU for local AI in 2026?</title><link>https://llamabuilds.ai/guides/rtx-3090-for-local-ai/</link><guid isPermaLink="true">https://llamabuilds.ai/guides/rtx-3090-for-local-ai/</guid><description>Six years on, a used RTX 3090 still gets you 24GB at 936 GB/s for about $1,050. How it stacks up against the RTX 5070 Ti, 5090, 7900 XTX, R9700 and more.</description><pubDate>Sat, 05 Jul 2025 00:00:00 GMT</pubDate><category>commentary</category><category>rtx-3090</category><category>nvidia</category><category>used-gpus</category><category>multi-gpu</category><category>buying-advice</category></item></channel></rss>