GMI Cloud
GMI Cloud is a Singapore-based GPU cloud platform that launched in 2023 with a clear focus: give AI teams direct access to high-end NVIDIA hardware without the enterprise sales friction that plagues larger incumbents. The pitch is straightforward — flagship GPUs, an API-first setup, and billing by the hour. If you’re running serious training runs or large-scale inference and need reliable access to H100s or H200s, GMI Cloud is worth a look.
The platform sits in an interesting middle ground. It’s not trying to be the cheapest option in the room, and it’s not yet the most feature-complete enterprise offering either. What it does offer is a clean, focused experience around the GPUs that actually matter right now for frontier AI workloads.
Why GMI Cloud stands out
GMI Cloud’s strongest selling point is hardware access. Offering both H100 SXM and H200 SXM configurations puts them in a relatively short list of providers where you can get the highest-tier NVIDIA silicon on demand — no waitlists, no lottery systems. For teams running large model training or multi-node inference at scale, that availability matters more than a few cents per hour.
The platform also has Blackwell-generation hardware on its roadmap, which signals that GMI Cloud is actively investing in staying current as the GPU landscape shifts.
Pros
- H200 SXM and H100 SXM available on demand — top-tier hardware without a waitlist
- Clean API with Docker support makes integration into existing MLOps pipelines straightforward
- Jupyter support for interactive workloads alongside headless API access
- Multi-GPU configurations supported for distributed training
- Persistent storage and reserved instances available for teams with predictable workloads
- Invoice-based billing alongside credit card — useful for companies that need purchase orders
Cons
- No spot instances, so there’s no way to trade reliability for cost savings
- No Kubernetes support limits orchestration options for teams running containerized fleets
- Not yet SOC 2 compliant — a non-starter for some regulated industries
- Founded in 2023, so the track record is shorter than established players like Vast.ai or RunPod
- Pricing competitiveness is middling — you’re paying for availability and hardware quality, not the lowest rate on the market
Getting started
- Visit GMI Cloud and create an account — credit card or invoice billing available
- Browse available GPU configurations via the dashboard or API catalog
- Spin up an instance with your preferred Docker image or use the Jupyter interface for exploratory work
- For recurring workloads, explore reserved instance pricing to lock in capacity and reduce per-hour costs
- Integrate the API into your training pipeline using their documentation
Best for: AI research teams and startups that need reliable, on-demand access to H100/H200 SXM hardware for training runs or large-scale inference, and are willing to pay a moderate premium for availability over rock-bottom pricing.