NEW Gemma 4 26B A4B Update

Want to make money and save time with AI? Join here: https://www.skool.com/ai-profit-lab-7462/about Video notes + links to the tools 👉 https://www.skool.com/ai-profit-lab-7462/about Get a FREE AI Course + Community + 1,000 AI Agents 👉 https://www.skool.com/ai-seo-with-julian-goldie-1553/about Google's new Gemma 4 26B A4B runs 10 simultaneous AI requests on a MacBook Pro — no API costs, no cloud dependency. This video breaks down the MoE architecture that makes it possible and exactly how to run it locally on consumer hardware today. 00:00 Intro – Why you're still paying for API calls you don't need to 00:20 What is Gemma 4 26B A4B? – The model overview 00:42 Gemma 4 vs Gemini 3 – Same foundations, open-source and free 01:14 Full model lineup – E2B, E4B, 26B A4B, and 31B Dense explained 01:52 MoE Architecture explained – Why only 4B of 26B parameters activate 02:32 Dense vs MoE – Speed and compute comparison 03:12 Hardware requirements – What you need to run it locally 03:36 Multi-instance inference – 10 concurrent requests on one laptop 04:28 256K context window – What that actually means in practice 04:39 Multimodal + thinking mode – Images, reasoning chains, and more 04:52 Agentic framework support – LangChain, LlamaIndex, JSON output 05:16 Best tools to run it – Ollama, LlamaC++, LM Studio, MLX 05:57 Known Apple Silicon issue – Flash attention fix for Gemma 4 06:11 Windows/Linux GPU guide – RTX 4090 and partial offload options 06:19 Try it free – No hardware? Use Google AI Studio 06:25 The big picture – What this shift means for local AI in 2025