Occamy-1.0 is aimed at 'co-work' agents — systems that gather information, call tools, write code and move files across many model invocations, where cost and latency accumulate over a whole episode. The authors built execution-grounded data and environments, captured replayable long-horizon trajectories, and used staged post-training on the post-trained Qwen3.6-35B-A3B checkpoint. Across a suite of co-work benchmarks, they report it is consistently among the strongest comparably sized models and competitive with substantially larger frontier systems on several tasks. Supporting evaluations in tool calling, coding and instruction following are said to preserve broad agentic capability. The model weights and a subset of the training data are released.