Run AI training and high-performance inference on NVIDIA H100, H200, Blackwell and Vera Rubin platforms are all available on-demand or through reserved capacity plans.
Run bare metal servers and container platforms
Deploy GPU clusters with full root control
Scale across GMI Cloud or private infrastructure
Train and run production AI workloads on dedicated NVIDIA GPU platforms inside GMI-operated data centers, optimized for predictable performance and sustained throughput.
Balanced performance for AI training and production inference.
Optimized for multi-purpose AI workloads
Stable latency under sustained traffic
Ideal for scalable LLM and multimodal inference
High-memory GPU for large-scale LLM workloads.
Extended memory for long-context models
Designed for large-batch inference
Reliable for production-scale deployments
Next-generation NVIDIA architecture for high-density AI clusters.
Built for next-gen training and inference
Improved performance-per-watt
Ideal for distributed cluster deployments
Best for: Multi-GPU distributed AI systems
Production fit: High-bandwidth interconnect for cluster workloads
Ideal workloads: Frontier model training and advanced inference
Best for: Long-context and high-capacity model training
Production fit: Built for next-generation multi-node clusters
Ideal workloads: Large-scale reasoning and high-density AI systems
Deploy fast and elastic AI workloads with our GPU-optimized container environments.
Rapid prototyping and experimentation
Elastic inference workloads
Internal AI services and pipelines
Fast startup
Elastic scaling
Kubernetes-based GPU environments
Dedicated physical servers for maximum performance and control.
Large-scale model training and fine-tuning
Long-running, high-utilization GPU workloads
Performance-critical inference
Full root access and hardware-level control
Predictable, isolated GPU performance
On-demand provisioning
Enterprise networking and SLA-backed delivery
Fully managed multi-node GPU clusters for distributed training and large-scale inference.
Enterprise AI and ML teams
Distributed, multi-node training
Organizations with existing GPU clusters
Centralized cluster lifecycle management
Unified management experience across environments
Supports managed clusters across both GMI Cloud and BYOS environments
Built for BYOS (Bring Your Own Service) and cloud-native deployments, with consistent performance, security, and operational guarantees.
Multi-region deployment across US, APAC, and EU
RDMA-ready networking for high-throughput workloads
Isolated VPC networking and enterprise-grade security
SLA-backed service delivery
Latest-generation GPU platforms
Cluster Engine can be used as a standalone GPU infrastructure platform, or as the foundation behind GMI Cloud's inference and training services, allowing teams to evolve their AI stack without switching platforms.
Explore Inference EngineTrend Micro uses GMI Cloud GPU clusters as a more cost-effective infrastructure foundation for AI-heavy workloads previously run on Oracle Cloud.
Mirelo AI uses GMI Cloud's dedicated GPU infrastructure to train foundational models with lower cost, faster iteration, and flexible commercial terms.
Magna AI works with GMI Cloud to support sovereign AI and government-focused deployment scenarios with infrastructure designed for controlled environments.
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