As of Sep 29, IQuest-Q1 is a 320B-parameter sparse-MoE model (about 15B active) reported by QbitAI, with demos spanning game generation, three-body equation solving and RL training-data debugging.
- Reported by QbitAI
IQuest-Q1: a 320B MoE model (15B active) that spots RL data bugs and builds games from prompts, per QbitAI
Not confirmed by the company — reported on Sep 29, 2026 (source: qbitai.com).
QbitAI reports IQuest-Q1, a decoder-only sparse-MoE model with about 320B total parameters and roughly 15B active. Demonstrations include generating a playable racing game from a single prompt, solving 100k-step three-body equations, and spotting a hidden-space bug in RL training data. QbitAI says it performs well on benchmarks including NL2Repo, CyberGym, Terminal-Bench 2.1, DeepSWE v1.1 and JobBench.
Source: QbitAI - Unconfirmed
IQuestLab/IQuest-Q1 · Hugging Face
Not verified by an official source as of Sep 29, 2026 (source: reddit.com).
A post on r/LocalLLaMA links the IQuestLab/IQuest-Q1 model page on Hugging Face.
Source: r/LocalLLaMA