https://llamay.com/blog/ Running language models on hardware you own. en https://llamay.com/blog/llama-cpp-alternatives-in-2026-and-when-each-one-is-the-righ/ https://llamay.com/blog/llama-cpp-alternatives-in-2026-and-when-each-one-is-the-righ/ Tue, 29 Sep 2026 00:00:00 +0000 Comparison llama.cpp is the reference for running GGUF models locally. Here is what Ollama, LM Studio, vLLM, MLX and llamay each do differently, and the job each one is the right answer for. https://llamay.com/blog/inference-bill-is-prefill/ https://llamay.com/blog/inference-bill-is-prefill/ Thu, 17 Sep 2026 00:00:00 +0000 Explainer Most teams price an LLM feature by output tokens and are surprised by the invoice. The prompt is the expensive half, it is usually identical every call, and there is a way to stop paying for it twice. https://llamay.com/blog/run-an-llm-locally/ https://llamay.com/blog/run-an-llm-locally/ Wed, 16 Sep 2026 00:00:00 +0000 How-to Five minutes from nothing to a model answering on your own hardware, plus the sizing table that decides whether you want a 3B, a 7B or a 70B. https://llamay.com/blog/how-to-cut-llm-latency-with-prompt-caching/ https://llamay.com/blog/how-to-cut-llm-latency-with-prompt-caching/ Wed, 16 Sep 2026 00:00:00 +0000 Guide How prompt caching skips the part of a prompt a model has already read, how to see it working in llamay, and what quietly defeats it. https://llamay.com/blog/ollama-vs-llamacpp-vs-llamay/ https://llamay.com/blog/ollama-vs-llamacpp-vs-llamay/ Tue, 15 Sep 2026 00:00:00 +0000 Comparison Three ways to serve a GGUF file on your own hardware, what each one is actually optimising for, and the one capability only one of them has.