Rebellions
Executive perspectives from Rebellions across NextGenInfra's event and research showcases.
2 video interviews · 2026
Making Inferencing Affordable at Scale
- Inferencing buyers have moved past benchmark tokens to production concerns: security, enterprise readiness, and economics.
- Rebellions' 4-kilowatt servers cut operating expense enough to support lower-cost service tiers and push inferencing unit economics toward zero.
- The newly released Rebel product ships alongside a partnership with AI&, an inference provider serving the Japanese market.
Abstract
Marshall Choy, CBO at Rebellions, explains how the AI inferencing industry is moving beyond performance benchmarks to focus on practical production needs like security, enterprise readiness, and economics, with Rebellions building energy-efficient 4-kilowatt servers that lower operating costs and enable affordable service tiers. He announces the Rebel product launch and a partnership with AI& to serve the Japanese market, positioning energy efficiency and cost reduction as essential for making AI inferencing accessible to organizations and applications that previously couldn't afford it.
Efficient AI Inference at Rack Scale
- Rebellions builds inference infrastructure end to end, pairing its in-house Rebel 100 accelerator with a software stack tuned for serving tokens economically.
- An open-source, no-fork software strategy lets customers keep their existing tools and models without learning new skills.
- Because inference is a rack-scale problem, most customers deploy Rebel Rack or Rebel Pod rather than individual servers.
Abstract
Jennifer Glore, EVP of Product Management at Rebellions, explains from the OCP event in San Jose how the inference infrastructure provider optimizes both hardware and software, pairing its power-efficient Rebel 100 accelerator with an open-source, no-fork software stack that lets customers run their existing tools and models. She describes how Rebellions packages these components into complete solutions, including Rebel Server, Rebel Rack, and Rebel Pod, with most customers choosing rack-scale deployments as global adoption grows.