Pavel Bushuyeu is a PhD student in the computer science department at the University of Hawaii, where he studies how skin cancer affects people of Pacific Island descent. One of a growing number of academics using AI to accelerate their research, Bushuyeu encountered a familiar obstacle: He must jostle with others on campus to get access to the school’s limited compute resources, while privacy and cost constraints make it difficult to use outside pay-by-the-hour compute services. Fortunately, he found a novel solution.
Earlier this year, Bushuyeu discovered a startup called B3 Labs that offers dedicated GPU hardware on a rent-to-own basis under the brand B3IQ. Under the company’s program, customers can pay 30% down on a variety of machines, including a frontier level Nvidia H200 rig that starts at $54,516, and spread out remaining payments over five years.
The option is an attractive one, says Bushuyeu, because the grant system that supports many university researchers typically requires that projects have predictable costs—a goal that is hard to meet when relying on rented compute, where prices can sway significantly.
A second advantage comes in the form of privacy. Owning a dedicated machine ensures researchers can comply with health-related laws like HIPAA, and avoid triggering the regulatory or national security concerns that go with relying on overseas compute providers. For practical purposes, B3IQ customers can arrange for the machine to be assembled on their own premises or, more practically, ask the company to host it at its 27,000-square-foot facility in Oregon.
