Machine Heart reports that SinapisAI, a startup incubated at Nanjing University, published a technical report titled "Toward Collective Model Intelligence," disclosing for the first time its framework for coordinating large numbers of models: quantified capability profiles for each model, a Mio router that picks and combines models based on task requirements and budget, and an underlying Model Space that manages versions and onboarding for 484 models. The report says Mio 1.0 Lite ranked first with a 77.15/100 average across nine public benchmarks at the lowest average cost of 0.06 yuan per request, and took top scores on five of the datasets; the figures are self-published and the account shows no independent reproduction. The report also acknowledges that cost-no-object flagship models retain a quality edge on hard tasks such as HLE, and that the overall benefit of integrating the system, along with the vision of collective intelligence improving with experience, still needs verification.