Agentic models that run on 32 GB
4 models with published weights that fit in 32 GB — a well-specified laptop. Counted at four-bit quantisation, weights only, leaving the machine about a third of its memory and a gigabyte for context: room for roughly 33 billion parameters. A mixture of experts is counted in full, because it is held in full even though only a few experts compute.
Enough for a thirty-billion-parameter model at four-bit with a long context, or a smaller one at higher precision if quality matters more than size. A practical ceiling for a laptop that also has to be a laptop.
- QwQ-32B-PreviewAlibaba32.0B≈20.8 GB at 4-bit2 also selling it hosted
- xLAM-2-32b-fc-rSalesforce32.0B≈20.8 GB at 4-bit1 also selling it hosted
- Qwen3.5-27BAlibaba27.8B≈18.1 GB at 4-bit8 also selling it hosted
- gpt2-xlOpenAI community1.6B≈1.0 GB at 4-bit