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9 pieces on local & open — practical workflows, case studies and field notes.

A new push to crowd-source real coding-agent transcripts, so open-weight models aren't locked out of agentic training data.

NVIDIA's new 550B reasoning model is the strongest US open-weights release yet — and it ships with the weights, the training data and the recipes. It's not the global frontier, but it's the most open one going.

Unsloth's new fine-tuning guide for Google's Gemma 4 open model family puts a bespoke model inside reach of small teams.

Google has quietly shipped an iPhone dictation app that runs speech-to-text on the device itself — no subscription, no audio leaving the phone. The trade-off against paid cloud tools.

Google's Gemma 4 models run on hardware a small business already owns — and they can see images, use tools and reason. Here's the plain-English guide: what's new, why it matters, and how to get started.

A 27B model that reportedly tops consumer-hardware leaderboards and fits in a single 24GB card at Q4. For a sole trader or a small professional-services team, that is the sweet spot worth understanding.

Both run open models on your own hardware. The right pick has less to do with benchmarks than with who on your team will actually be using it.

AMD's software stack spent years as the awkward alternative to NVIDIA. In 2026 it is a credible cost play for a back-office team — provided you check a few things first.
May 2026's runtime updates look like housekeeping. For a solo operator running models on a MacBook, they quietly remove some of the friction that makes local AI feel like hard work.