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IQuest-Q1

Open-weight agentic coding model from IQuestLab with a 524,288-token context, for teams that self-host

About IQuest-Q1

IQuest-Q1 is an open-weight model from IQuestLab, the team behind the IQuest-Coder models. It is aimed at coding agents, reasoning and tasks that chain several tool calls. It was published on Hugging Face on 28 September 2026, and every benchmark result is IQuestLab's own.

What IQuest-Q1 does

  • Agentic coding: aimed at coding agents that carry out several steps, including tool calls.
  • Long context: a 524,288-token window, with full-attention layers spaced among sliding-window layers to keep long inputs affordable.
  • Mixture of experts: about 320 billion parameters, with 15 billion active per token across 8 of 256 experts.
  • Faster output: multi-token-prediction layers speed up decoding.
  • Self-hosting: the model card gives configurations for SGLang and vLLM, and names no hosted API.

Clients

Teams that want to self-host a text model in English and Chinese for coding and tool use.

Key facts

  • Developer: IQuestLab (IQuest Research).
  • Published: 28 September 2026 on Hugging Face.
  • Languages: English and Chinese text only.
  • Licence: modified MIT. Any commercial product built on the model must prominently display IQuest-Q1 in its user interface.

Profile written by TrustList from the business's own published information, Oct 2026.

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