--- title: NightRun UEFI application boots a local LLM on Raspberry... description: NightRun is an experimental open-source UEFI application that boots a local LLM directly from a USB drive or microSD card without any conventional operating... canonical: https://daily.dev/posts/nightrun-uefi-application-boots-a-local-llm-on-raspberry-pi-5-and-x86-pcs-without-an-os-4vcw3e8ej twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: NightRun UEFI application boots a local LLM on Raspberry Pi 5 and x86 PCs without an OS | daily.dev og:description: NightRun is an experimental open-source UEFI application that boots a local LLM directly from a USB drive or microSD card without any conventional operating... og:url: https://daily.dev/posts/nightrun-uefi-application-boots-a-local-llm-on-raspberry-pi-5-and-x86-pcs-without-an-os-4vcw3e8ej og:image: https://api.daily.dev/og/posts/4VCw3e8Ej.png og:image:alt: NightRun UEFI application boots a local LLM on Raspberry Pi 5 and x86 PCs without an OS og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # NightRun UEFI application boots a local LLM on Raspberry Pi 5 and x86 PCs without an OS **[CNX Software](https://daily.dev/sources/cnx-software)** · 3 min read · 0 upvotes · 0 comments ## Summary NightRun is an experimental open-source UEFI application that boots a local LLM directly from a USB drive or microSD card without any conventional operating system. Written in Rust, it eliminates the OS layer entirely — no Linux kernel, scheduler, or network stack — freeing up RAM and memory bandwidth for AI inference. It supports x86_64 UEFI PCs and Raspberry Pi 5, and can run quantized models including Llama 3.2 1B/3B, Granite 4.1 3B, and Qwen3 4B. Models are loaded into RAM at boot with CRC-32 verification, and storage is sealed afterward. Inference uses AVX2/FMA/F16C on x86 and NEON on ARM. Performance on an 8GB Raspberry Pi 5 reaches ~3 tokens/sec for a 3B model. A built-in framebuffer chat UI is included. The project is MIT-licensed and available on GitHub. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [There's no Linux on my Raspberry Pi anymore — it boots straight into a local LLM instead](https://daily.dev/posts/there-s-no-linux-on-my-raspberry-pi-anymore-it-boots-straight-into-a-local-llm-instead-wel5wley5) · XDA Developers · 0 upvotes · 0 comments - [Running LLMs on Raspberry Pi and Edge Devices](https://daily.dev/posts/running-llms-on-raspberry-pi-and-edge-devices-vywckugzb) · SitePoint · 1 upvotes · 0 comments - [AlexsJones/llmfit: Hundreds of models & providers. 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