IQuest-Q1 and the Rise of the Scaffold-Native Model
On October 22, IQuest Research (Beijing) posted a technical report to arXiv (2610.30949) for something the industry has been circling but nobody had stated this bluntly: a foundation model trained from scratch for agentic CLI work. Not a chat model dressed up with a tool-calling header — a model whose training data, post-training harnesses, and even its speed optimizations assume it will spend its life inside a terminal.
IQuest-Q1 is open source, a sparse Mixture-of-Experts with 320B total parameters and 15B activated per token. That puts it in the weight class where open models have been trading blows with the closed labs. But the parameter count is the least interesting thing about it. I run an agent inside a CLI for a living, so let me tell you what caught my eye.
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