AI
Everything we publish on AI: the models we run on our own machines, what the tools send home, the benchmarks we measure ourselves and the claims we check against the code. Start with the investigations, then the guides.
gemmaHow to run Gemma 4 12B locally on a Mac with Ollama
How to run Gemma 4 12B locally on a Mac with Ollama: the pull command, the memory it needs, the…
local-aiWhat the Ollama MLX shift means for local AI on Mac
Ollama is moving toward MLX on Apple Silicon. What the shift changes for speed, memory and model choice, and whether…
assistantOpenClaw with a local model: a private AI assistant
Run OpenClaw with a local model and keep a persistent AI assistant on your own machine. Onboarding, memory, tools, and…
comfyuiComfyUI with local LLMs: a practical Mac workflow
Wire local LLMs into ComfyUI to write better prompts. The nodes, the model, the memory cost on a Mac, and…
local-aiHow we built our local AI stack at Stridenote
The local AI stack we run at StrideNote on an M4 Pro: the models, the server, the agents, and the…
coding-agentsHow to Set Up a Local AI Coding Agent on a Mac
A step by step setup for a local AI coding agent on a Mac. No rate limits, no credits, no…
benchmarksBest Local LLMs for Coding on a Mac in 2026: Benchmarked and Ranked
We benchmarked and ranked the best local LLMs for coding on a Mac in 2026, on real refactors, with speed,…
cloud-aiPrivacy-first coding: why you should run AI agents entirely offline
Your config files hold keys and endpoints. Here is why we run AI agents offline, what a cloud agent can…
lm-studioHow to choose between Ollama, LM Studio, and MLX for local models
Three ways to serve a local model on a Mac. We compare Ollama, LM Studio and MLX on setup, speed…
coding-agentsOpenCode with a local model: set up an offline AI coding agent
Point OpenCode at a local model and code with no internet and no API key. The setup, the config, and…