Quota Marketplace: Dynamic Pricing for Efficient Allocation of ML Training Resources

Jul 14, 2026

Google researchers introduce Quota Marketplace, a market-based system for allocating ML training chips such as GPUs using dynamic pricing to accommodate workloads with varying values. The system, implemented and deployed at Google, is designed to achieve Pareto efficiency and max-min fairness, and to better align resource allocation with organizational priorities. The paper details both the theoretical foundations and practical deployment, including metrics demonstrating its impact.

Why it matters: Efficient allocation of scarce ML training resources is a major challenge for organizations, and this work demonstrates a practical, scalable solution that addresses heterogeneous workload values.

Full story at: arXiv Machine Learning ↗