A local model on a Mac sounds cheap until you read the RAM line.
Meta launched Muse Spark Open, an open-weight multimodal model designed to run on Apple silicon, according to TechCrunch. It has an 816B parameter size and a 1M token context window, but local use reportedly needs at least 1TB of RAM and is best aimed at a Mac Studio with M5 Ultra.
My angle for small business automation
I'd say this honestly: this is not for a cafe owner replacing Zapier next week. But the direction matters. For support, invoices, legal documents, OCR review, warehouse reports, and internal search, open-weight local models mean fewer per-token surprises and less data leaving the company. The practical setup today is still hybrid: Claude or API models for hard reasoning, smaller local models for classification, extraction, draft replies, and custom code around the workflow. n8n fits when the flow is simple; the real value is in the pipeline and guardrails, not demo videos.
Why it matters: Local AI is becoming a privacy and cost option, not just a lab toy. The catch is hardware and maintenance - it pays for itself only when it removes enough manual document or support hours.
Source: TechCrunch