Accio Lab publishes Occamy-1.0 weights, a 35B co-work agent model post-trained from Qwen3.6-35B-A3B

Hugging Face (via r/LocalLLaMA, 87 upvotes; paper arxiv.org/abs/2609.11977)·medium signalXBlueskyLinkedInCopy link

The Hugging Face repo Accio-Lab/occamy-1.0 was last modified 2026-09-16 and carries 93 likes and 1,048 downloads against the paper arXiv:2609.11977, 'Occamy-1.0: Open Pareto-frontier 35B Intelligence for Co-work' (dated 2026/09/04). It is Apache-2.0, a Qwen3_5MoeForConditionalGeneration image-text-to-text MoE, and the paper's pitch is cost-per-episode rather than peak capability: co-work agents spend most steps on state tracking, coordination, recovery and follow-through, not frontier reasoning, so they trained execution-grounded replayable long-horizon trajectories across multiple harnesses. Useful if you are paying for a long agent loop rather than a single hard question.