Author: Julian Goldie SEO - Bewertung: 1x - Views:41
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Gemma 4 + the new Ollama update turn your laptop into a real coding agent — no internet, no API bill, no data leaving your machine. I break down what actually changed, which of the 6 model sizes to pull (the obvious pick is wrong), and the benchmarks showing local models jumped a full tier. Plus how I run it all inside Agent OS with a local memory vault.
00:00 Intro – Why local coding agents just got good
00:40 Ollama vs Gemma 4 – The confusion costing you hours
01:01 What Makes Gemma 4 Different – Multimodal, reasoner-by-default
01:25 Thinking Modes – Dial reasoning up or down on demand
01:41 Context Windows – 128K vs 256K, and which you need
01:51 Native Function Calling – The feature that turns chat into agent
02:09 System Prompt Support – More control across a full session
02:17 All 6 Model Sizes Compared – Disk space, context, tradeoffs
02:52 The Model I'd Pull First – Smaller file, double the context
03:01 Where People Get Stuck – Agent OS + live setup help
04:05 Benchmarks: Reasoning – MMLU Pro, GPQA, AIME 2026
04:20 Benchmarks: Coding – LiveCodeBench 29% → 80%
04:58 Vision + Tiny Models – Even E2B beats last-gen 27B
05:15 Long Context Reality Check – Big window ≠ big recall
05:32 Ollama 0.32.1 Update – The tool-calling fix that changes everything
06:02 What I Built – Websites, a mini app, and a game
06:17 Agent OS + Obsidian – Local model, local agent, local memory
06:40 Pro Tips – 5 mistakes that ruin your first night
07:34 Free Resources – AI Success Lab + video notes
07:50 The Wall You'll Hit – And how to get through it fast