QuantumScape announced its QS PowerBlock on October 8, 2026, introducing a modular solid-state lithium-metal battery reference design for AI data centers. The system targets in-rack energy storage and supports emerging 800 VDC power architectures.
According to the company, prototype testing and modeled system configurations demonstrated up to four times the power density and five times the runtime compared with benchmarks based on the Open Compute Project (OCP) Open Rack V3 specification.
Higher Power Density for AI Data Center Racks
QS PowerBlock is designed for different module, shelf, and rack configurations. QuantumScape says the technology could support high-density computing environments, including future 1 MW server racks.
The design addresses two requirements: delivering high power within limited rack space and providing sufficient runtime to manage short-duration power fluctuations.
These requirements also affect the design of AI data center UPS infrastructure, although in-rack battery systems and centralized data center UPS systems use different electrical architectures.
Solid-State Battery Safety
QuantumScape also reported that its solid-state battery cells demonstrated thermal stability above 300°C in third-party and customer testing.
These results concern individual battery cells under specific test conditions. They do not establish the fire performance or certification status of a complete rack-mounted battery system.
For UPS battery safety, system-level protection remains important, including monitoring, thermal management, electrical isolation, and fault protection.
Implications for UPS Power Systems
QS PowerBlock highlights a developing approach to data center backup power: placing high-performance batteries closer to computing equipment.
However, in-rack energy storage does not automatically replace centralized UPS installations. The appropriate architecture depends on load characteristics, required backup time, redundancy, DC distribution, and maintenance requirements.
QuantumScape has stated that its performance comparisons are based on prototype tests and modeled configurations. Commercial system performance will depend on the final design and operating conditions.
The announcement adds another technology option for AI data center power infrastructure, while leaving system integration and commercial validation as important next steps.
