Blog · 2026-10-13

Launching UnifiedMem: sourced local AI setups for your Mac

Why we built a Mac-only, sourced, config-first resource for running local LLMs and coding agents.

Researched and drafted with AI assistance from the cited sources. Benchmarks are single-machine third-party results: treat them as indicative, not guaranteed.

Running LLMs locally on a Mac got a lot better in 2026. oMLX went from nothing to ~22.7k GitHub stars in months, Ollama shipped a native MLX runner, and Qwen3.6-35B-A3B made a strong coding model practical on a 32 GB laptop.

It’s also confusing. The most common complaints are slow prefill on long agent prompts, KV caches that get thrown away, swap cliffs, and defaults like a 262k context that more than doubles memory use.

UnifiedMem exists to answer one question: for my chip and RAM, what exact model, server and agent config works?

What you’ll find here:

• Guides: oMLX tuning, choosing a quant, a slowness troubleshooting tree, local Claude Code/OpenCode, and LoRA fine-tuning.
• Directory: runtimes and models compared, every number sourced.
• Shop: copy-paste config packs, prompt packs and notebooks.
• Newsletter: weekly, short.

How we work: this site is run with substantial AI assistance under human oversight, and every factual claim links a source. If something is wrong, tell us.

Skip the trial and error: sourced config packs →