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Maximale Performance für HPC- & KI-Workloads mit der NVIDIA H100 GPU: Exascale-Unterstützung, Transformer Engine, Multi-Instance-GPU (MIG) & Test Drive Programm
Sysgen is currently under verification. Profile data reflects publicly available information and is subject to change as operator verification completes.
Check back once verification is complete for a more detailed read.
For multi-node runs where interconnect and cluster availability decide the outcome.
Best for
Mature training stacks that value known performance and broad tooling support.
Best for
Training and inference for teams evaluating the AMD ecosystem.
Best for
Serious model training where time-to-result outweighs hourly cost.
Best for
Frontier-scale training and the highest-throughput inference workloads.
For predictable production serving, latency targets, and steady utilisation.
Best for
GB300 workloads.
Best for
B300 workloads.
Best for
Production serving for models that fit in 48 GB without SXM pricing.
Best for
Cost-effective production inference and image generation at scale.
For smaller adaptation jobs, evaluation loops, and budget-controlled development.
Best for
Development and fine-tuning with 48 GB of memory at workstation pricing.
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