H200
Rent NVIDIA H200 GPU
H200 GPU: 141 GB HBM3e, Hopper architecture. Explore workload requirements and check rental availability in GlobalAtlas AI Console.
Choose a configuration in Console to review its resources and estimated cost.
What to plan for
141 GB is GPU memory, not system RAM. Confirm the number of GPUs and required interconnect before choosing a training topology.
Size weights, runtime buffers and data separately. The host also needs CPU, RAM, disk and a suitable region. No rental price or availability is implied by this hardware specification.
What this GPU can be used for
Memory-intensive LLM inference and scientific computing. Plan within the 141 GB memory budget after accounting for runtime overhead. The exact software stack determines which workload is suitable.
Popular deployment scenarios
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Explore →AI training
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Explore →Check availability: H200
Check the current price and configuration in Console. Your choice is saved through registration. The current lookup uses mock adapters; no real capacity is reserved.
Before you deploy
Is this GPU available right now?
The hardware page is permanent. Console checks the current adapter offers; if none match, it shows alternatives and lets you retry.
Does VRAM determine application performance?
No. Model, precision, context, software and batching matter. Measure your workload before committing to a configuration.
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GPU cloud
Compare GPU memory and architectures, from RTX to data-center accelerators, then check configurations in one console.
Explore →Compare GPU specifications and pricing
Compare GPU memory size, memory technology and architecture across the GlobalAtlas AI hardware catalog.
Explore →H100
80 GB HBM3 · Hopper
Explore →A100
80 GB HBM2e · Ampere
Explore →Specification sources
Hardware and model documentation; these sources do not confirm rental availability.
Official documentation 1 →