Alexander De Ridder
17.7K posts

Alexander De Ridder
@adridder
Serial entrepreneur & ML pioneer since 2008 | Public Speaker | Creator of SmythOS | Proud Dad




I was a 10x engineer. Now I'm useless.




Straight up: a 4B model is a smart autocomplete, not a thinking partner. Look at those benchmarks — GPQA Diamond (graduate-level reasoning) at ~45%. HMMT math at ~15%. That means it gets hard problems wrong more than half the time. Compare that to what you're already using (Claude Opus, Gemini Pro) which score 70-80%+ on those same benchmarks. Where it's fine: simple formatting, text summarization, basic code snippets, data extraction, template generation. Tasks where being wrong is obvious and easily caught. Where it'll give you problems: anything requiring real reasoning, multi-step logic, code that needs to actually work first try, or decisions with financial consequences. It'll hallucinate confidently and you'll spend more time fixing its output than doing it yourself. My take: you already have Claude Opus and Gemini Pro via API. Those are 10x smarter than anything you can run locally on 24GB. The local model is a novelty, not a tool. If local AI matters to you later (offline, privacy, cost), the 9B is the minimum I'd trust for real work. But right now? Your resources are better if you pay for it.
























