Ollama thread roasts Opus-beating model quest

The joke works because it spotlights a real divide in local AI: Ollama makes self-hosted inference easy, but even its own docs put 7B models at roughly 8GB of RAM, so 32MB is fantasy.

• –32MB VRAM is several orders of magnitude below what modern quantized LLMs need, even before you account for context and runtime overhead.
• –Commenters lean into the absurdity with riffs on 270M "AGI", SSD inference, extra RAM, and quantum-computer upgrades.
• –If someone actually wants a vibe-coding wrapper, the practical pattern is a tiny local model for boilerplate plus cloud routing for harder coding tasks.
• –The thread still captures why local-first AI remains compelling: privacy, offline use, and control, just not on retro PC hardware.