Maximum AI throughput
80 GB HBM3, 3 TB/s memory bandwidth, up to 1,456 TFLOPS TF32 and 3,456 tensor TFLOPS, with 900 GB/s NVLink connectivity.
Accelerate insight at every scale.
Professional NVIDIA accelerators provide the memory capacity, interconnect bandwidth and specialized compute engines behind production AI and high-performance computing.
Accelerated ComputingNVIDIA H100 NVIDIA L40S NVIDIA A100 Deployment
Professional NVIDIA GPUs for AI and HPC.
A production GPU platform is a complete system decision. Model size, numerical precision, memory bandwidth, GPU-to-GPU communication, cooling and software support must work together. SmartComm architects qualified systems from visualization-class inference nodes to dense multi-GPU training clusters.
From model development to scientific discovery
- AI training and inference
- Computer vision
- Natural language processing
- Quantum simulation
- Molecular modeling
- Climate simulation
- Financial modeling
- Scientific visualization
Technical specifications
Versatile visual compute
48 GB GDDR6 ECC, 864 GB/s memory bandwidth, up to 568 TFLOPS FP32 and third-generation RT cores for AI, rendering and media.
Proven data center acceleration
40 GB or 80 GB HBM2e, up to 19.5 TFLOPS FP64 and 312 TFLOPS TF32, with up to 600 GB/s interconnect bandwidth.
Qualified integration
PCIe and dense accelerator configurations with validated power, airflow, host memory, high-speed networking and enterprise NVIDIA software options.
Configuration guidance
Start with model or simulation memory demand, then size precision throughput, inter-GPU communication and scale-out fabric.
| Workload profile | Recommended GPU | Configuration focus |
|---|---|---|
| Foundation model training | NVIDIA H100 80 GB | Multi-GPU nodes, NVLink and high-bandwidth scale-out networking. |
| Inference and digital content | NVIDIA L40S 48 GB | High-density inference, graphics, rendering and video pipelines. |
| Established AI / HPC | NVIDIA A100 40 / 80 GB | Proven CUDA environments, mixed precision and FP64 scientific work. |
Platform positioning
Match capability to utilization
H100 leads for large-scale AI training and tightly coupled workloads. L40S provides a strong balance for inference, graphics and media, while A100 remains a proven option for mature CUDA and scientific environments. Right-sizing memory and interconnect often creates more value than selecting on peak compute alone.