# Facing High GPU Costs and Infrastructure Constraints, Amberd Turned to QumulusAI for Fixed-Cost AI

Published 2026-02-18 · Updated 2026-06-22 · Engineering & Construction on MarketScale
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Creator hub: QumulusAI

> Managed AI service providers are discovering how to escape unpredictable infrastructure costs by moving beyond hyperscaler pricing models

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Providing managed AI services at a predictable, fixed cost can be challenging when hyperscaler pricing models require substantial upfront GPU commitments. Large upfront commitments and limited infrastructure flexibility may prevent providers from aligning costs with their delivery model.

> Providing managed AI services at a predictable, fixed cost can be challenging when hyperscaler pricing models require substantial upfront GPU commitments.

[Amberd](https://amberd.ai/) CEO **Mazda Marvasti** encountered this issue when exploring GPU capacity through Amazon. The minimum requirement was an eight-GPU commitment totaling roughly $40,000 per month — an investment that did not support his company's pricing structure. He also found that the surrounding infrastructure lacked the customization needed to properly run his platform across customers. Partnering with **QumulusAI** allowed his team to architect an environment tailored to their technical requirements, ultimately enabling **Amberd** to deliver AI services at a consistent, fixed monthly cost.

> Partnering with QumulusAI allowed his team to architect an environment tailored to their technical requirements, ultimately enabling Amberd to deliver AI services at a consistent, fixed monthly cost.

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