GMI Cloud
An inference-first GPU cloud platform combining serverless inference and dedicated GPU infrastructure for production AI workloads, built on NVIDIA hardware.
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Product Overview
What is GMI Cloud?
GMI Cloud is an AI-native cloud platform purpose-built for production AI inference and training. It offers a unified stack that spans serverless inference, Kubernetes-based cluster orchestration, and bare metal GPU compute — all on NVIDIA H100, H200, and upcoming Blackwell GPUs. The platform is designed to eliminate the overhead typical of hyperscalers, recovering 10–15% of GPU performance lost to virtualization while offering transparent, pay-as-you-go pricing with no quotas or long-term commitments. As an NVIDIA Cloud Partner, GMI Cloud provides priority access to cutting-edge GPU hardware with enterprise-grade security and global availability across US, EU, and APAC regions.
Key Features
Serverless Inference Engine
Deploy AI models instantly with automatic scaling, built-in request batching, and latency-aware scheduling — including scale-to-zero to eliminate idle costs.
Dedicated GPU Cluster Engine
Kubernetes-based orchestration environment for managing scalable GPU workloads, with real-time monitoring, container management, and secure multi-tenant isolation.
High-Performance GPU Compute
On-demand access to NVIDIA H100 and H200 GPUs with InfiniBand networking, delivering near-bare-metal performance with no quota restrictions and no waitlists.
Per-Request Inference Pricing
100+ pre-deployed models available at per-request rates from $0.000001 to $0.50/request, enabling cost-efficient inference without long-term contracts.
Enterprise Security & Compliance
Deployed in Tier-4 data centers with SOC 2 Type 1 and ISO 27001:2022 certifications, ensuring high availability, data security, and regulatory compliance.
Use Cases
- Real-Time LLM Serving : Teams running open-source models like Llama or DeepSeek can serve them at ultra-low latency with automatic traffic scaling via the Inference Engine.
- Large-Scale AI Training : Research and engineering teams can run distributed training jobs across multi-node GPU clusters with RDMA-ready InfiniBand networking for maximum throughput.
- AI Startup Infrastructure : Early-stage teams can start serverless with zero upfront cost, then migrate to dedicated GPU infrastructure as production workloads grow — without re-architecting.
- Enterprise AI Deployment : Enterprises requiring predictable performance, compliance, and cost control can leverage dedicated bare metal GPUs with commitment-based pricing discounts.
- Multimodal Model Inference : Production-ready APIs support both LLM and multimodal model deployments, covering a wide range of inference workloads from text generation to vision tasks.
FAQs
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