rewrite this title Boundless Expands Distributed GPU Compute Network To Support AI Inference Workloads | Metaverse Post

by
Alisa Davidson

Published: July 14, 2026 at 10:26 am Updated: July 14, 2026 at 10:26 am

by Anastasiia O

Edited and fact-checked:
July 14, 2026 at 10:26 am

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Boundless has announced its expansion into the artificial intelligence sector, with plans to deploy its distributed GPU network to support the growing demand for AI inference. The move extends the company’s existing infrastructure, which was originally developed to power zero-knowledge (ZK) proving workloads for the cryptocurrency industry.

“Four years ago, we set out to solve one hard compute problem,” said Shiv Shankar, CEO of Boundless. “In the process, we built something bigger: a network for coordinating distributed GPU capacity. AI now needs the same foundation at a much larger scale. Open models are giving teams more control over what they build, but production inference is still constrained by cost, capacity, and reliability. Boundless is built to change that.”

The company’s ZK proving network was designed to coordinate distributed GPU resources, schedule compute-intensive tasks, and maintain efficient operations across multiple machines. Boundless stated that the same infrastructure is now being adapted to address increasing demand for AI inference as organizations expand the deployment of artificial intelligence applications.

According to the company, AI inference is emerging as a significant driver of computing demand, with infrastructure costs becoming an increasingly important consideration. Citing Gartner, Boundless noted that 55% of spending on AI-optimized infrastructure-as-a-service is expected to be allocated to inference in 2026, increasing to more than 65% by 2029.

Boundless Repurposes GPU Network for AI Inference

Boundless stated that many AI inference workloads do not require premium data center GPUs and can instead operate efficiently on lower-cost hardware, including consumer-grade graphics processors and GPUs originally acquired for compute-intensive applications such as cryptocurrency mining and ZK proving. The company said it aims to identify and optimize this underutilized capacity by integrating hardware, software, and inference-serving systems.

The company currently operates a distributed network of approximately 4,000 GPUs that was initially developed for ZK proving. As part of its AI strategy, Boundless is optimizing the network to provide managed inference infrastructure, including hardware optimization, workload adaptation, routing, batching, scheduling, monitoring, and operational support.

Boundless reported that early benchmarking indicates inference costs could be reduced by as much as 50% compared with hyperscale cloud providers, with the greatest potential savings expected for asynchronous workloads. The company also plans to integrate its native ZKC token into the AI network, with operators expected to stake the token to participate and with staking levels linked to earning potential.

Boundless stated that the expansion is intended to enable organizations to deploy AI inference workloads with lower computing costs. The transition to AI infrastructure was announced today, while the full product launch is scheduled for later this summer. The company added that it will continue operating its zero-knowledge proving network alongside its AI inference services.

Alisa, a dedicated journalist at the MPost, specializes in crypto, AI, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.

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