METASTONE launches TokenFleet inference cluster scheduling framework
At the 2026 CCF National High Performance Computing conference, METASTONE (是石科技) released TokenFleet, a distributed scheduling framework focused on request routing, cross-datacenter capacity coordination and mixed-workload governance. The framework combines TokenPilot for instance selection, FleetMind for cross-datacenter capacity coordination and SLOMax for admission, queue governance and capacity allocation by service tier. METASTONE says that on its GLM5.3 tuning data, under the tested GPU cluster and workload, predictive-latency routing cut P95 time-to-first-token by 32.4% and P50 by 71.3%, while an SLOMax example estimated about 29.4% higher goodput; the report notes these are vendor measurements and that lower latency does not directly mean lower cost.
The release targets a cluster-level problem METASTONE describes as queuing and idle capacity occurring at the same time, aiming to raise effective token output from existing GPU capacity.
首Token延迟降低32.4%!是石科技集群调度大招,国产推理再提效 – 量子位
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首Token延迟降低32.4%!是石科技集群调度大招,国产推理再提效

最新发布TokenFleet调度框架
#METASTONE#TokenFleet#TokenPilot#FleetMind#SLOMax#GLM5.3#Meta-Infer