Hyperscaler Exit
5 articles
Articles
9 February 2026
High-Performance Alternatives to AWS SageMaker for AI Teams
AWS SageMaker AI combines compute with managed development, training and deployment features. A cheaper alternative depends on which of those features your team uses and the engineering work needed to replace them. Compare matched hardware, region, purchasing term and utilization, then include storage, transfers, migration and operations. Specialized GPU clouds can be an alternative for containerized training or inference, while teams that rely on SageMaker Pipelines, data tooling or managed endpoints may value the integrated service. Lyceum publishes this article and competes in this market.
4 May 2026
Hyperscaler GPU Alternatives in Europe: The Infrastructure Guide
Expiring cloud credits and chronically underused GPU capacity are breaking unit economics for AI startups. Engineering leaders are migrating to specialized European infrastructure to cut costs and guarantee GDPR compliance.
2 May 2026
Azure GPU Pricing Alternatives 2026
The initial wave of hyperscaler credits has dried up. Discover how AI startups are cutting compute costs while maintaining strict EU data sovereignty.
23 February 2026
ML Training Without AWS: A Guide to Sovereign GPU Infrastructure
Hyperscalers often trap ML teams with high egress fees and complex orchestration that leads to chronically low GPU utilization. Transitioning to a sovereign GPU cloud allows for better resource efficiency, support for GDPR compliance, and a significant reduction in the total cost of compute.
11 February 2026
Beyond the Big Three: Optimizing ML Training on Alternative Clouds
Legacy hyperscalers charge a premium for general-purpose infrastructure that often leaves GPUs idle and budgets drained. Moving to specialized ML infrastructure reduces egress fees and eliminates the DevOps tax while maximizing hardware efficiency for large-scale training runs.