Developers Build Linux GPU Driver for M4 Mac mini in a Month Using Coding Agents

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Two developers, Cody Ho and Niklas Sheth, released a working OpenGL ES 3.0 conformant Linux GPU driver for the M4 Mac mini and MacBook Neo in September 2026. Most of the code was written by LLM coding agents, with Codex handling kernel and firmware reverse engineering and Claude handling user-space work. The driver ships in Gravity Linux, a Fedora remix forked from Asahi Linux, whose AI policy permits generative AI under disclosure rules while Asahi's forbids it. The team reports building the driver from live hardware traces rather than Apple binaries, reusing Asahi's kernel UAPI while writing new code, including a custom shader compiler. The project also relied on Khronos conformance tests to ground the agents, though it required notable human judgement, such as changing capture methods after an agent spent over a week on an unreplayable trace.

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Roku Moves Developer Repositories from GitHub to GitLab

Roku has relocated its developer code repositories from GitHub to GitLab, according to a company blog post. The announcement was shared on Hacker News, where it gathered 14 points and one comment. The source material provides few additional details about the timing or the reasons behind the switch. Developers who rely on Roku's repositories may need to update their links and workflows to reflect the new hosting location.

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ProgrammingHacker News ·

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ProgrammingDEV Community ·

DeepSeek-Linked Paper Proposes Engram, a Lookup Memory Module for Transformers

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ProgrammingDEV Community ·

Guide: Running a 4B Qwen3 Chat Model Locally on Windows with a Small NVIDIA GPU

A DEV Community guide explains how to run the 4-billion-parameter Qwen3-4B chat model on a Windows PC with an NVIDIA RTX 30, 40, or 50 series GPU, using a prebuilt zip from the author's open-source Pingala-8 project. The only required install is a recent NVIDIA driver, since the package bundles the CUDA runtime files and avoids the full CUDA Toolkit and any compilation. Users extract the zip and run a batch script that downloads the roughly 1.24 GB model from Hugging Face on first launch, then starts a local llama.cpp server and opens a browser-based chat page at 127.0.0.1:8080. The author reports about 200 tokens per second on an RTX 5070 Ti Laptop GPU and notes that the setup requires roughly 5 GB of free disk space and an internet connection for the initial download.

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