<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>tudalex blog</title><description>Consulting from an ex-FAANG tech lead on private, self-hosted AI and software architecture: LLMs on your own hardware, on-device models for apps, private RAG, and system design reviews.</description><link>https://tudalex.com/</link><item><title>Splash vs Ollama vs MLX on an M4 Max: is “2× faster” real?</title><link>https://tudalex.com/blog/splash-vs-ollama-vs-mlx/</link><guid isPermaLink="true">https://tudalex.com/blog/splash-vs-ollama-vs-mlx/</guid><description>I benchmarked the new Splash inference engine against Ollama and Apple&apos;s mlx-lm with Qwen 3.8 27B, from an empty context to 200K tokens. Writing code gets 2–5× faster. Reading long prompts doesn&apos;t.</description><pubDate>Thu, 08 Oct 2026 00:00:00 GMT</pubDate></item><item><title>bicameral: Claude does the thinking, a local model does the typing</title><link>https://tudalex.com/blog/bicameral/</link><guid isPermaLink="true">https://tudalex.com/blog/bicameral/</guid><description>An open-source tool that lets Claude Code hand mechanical work to an open model on your own machine. Free tokens, files that stay local, and Claude still checks the result.</description><pubDate>Wed, 07 Oct 2026 00:00:00 GMT</pubDate></item><item><title>When does it make sense to run LLMs on your own hardware?</title><link>https://tudalex.com/blog/when-to-run-llms-locally/</link><guid isPermaLink="true">https://tudalex.com/blog/when-to-run-llms-locally/</guid><description>A practical checklist for deciding between a hosted API and self-hosted open-weight models — and the hidden costs on both sides.</description><pubDate>Wed, 07 Oct 2026 00:00:00 GMT</pubDate></item></channel></rss>