ZGCM-1 is a fully open 7B whose training cluster was operated by agent swarms.

arXiv 2609.13356, 227 HuggingFace upvotes, releases a 7B dense model trained from scratch on the premise that small models can't memorize the web but can trade parametric capacity for deliberate thinking plus external tools. Fully open recipe: interleaved gated sliding-window and full attention, an FP8 Muon optimizer, a progressive curriculum scaling context through 16K, 64K and 256K while reformulating interaction traces as MDPs. On math reasoning and agentic search it stays competitive with Qwen3-235B-A22B and GLM-5.1. The authors report agent swarms autonomously handling cluster operations, data curation and diagnostic evaluation during the run.