NVIDIA Hopper H200 / H100
The industry-standard AI accelerators for enterprise training and inference. H100 delivers proven reliability with 80GB HBM3 and the Transformer Engine, while H200 extends memory capacity to 141GB HBM3e for larger models. Both feature 4th-gen Tensor Cores and 900GB/s NVLink for multi-GPU scaling.
Why Choose Hopper
Proven architecture trusted by thousands of enterprise deployments worldwide
Hopper Configurations
Choose the right Hopper GPU for your workload requirements
Technical Specifications
Complete Hopper H100 and H200 technical details
| Specification | H100 PCIe | H100 SXM5 | H200 SXM |
|---|---|---|---|
| Architecture | |||
| GPU Architecture | NVIDIA Hopper (GH100) | ||
| Process Node | TSMC 4N (Custom 4nm) | ||
| Transistors | 80 Billion | ||
| Compute | |||
| Streaming Multiprocessors | 114 | 132 | 132 |
| CUDA Cores | 14,592 | 16,896 | 16,896 |
| Tensor Cores | 456 (4th Gen) | 528 (4th Gen) | 528 (4th Gen) |
| Transformer Engine | Yes (FP8 support) | ||
| Memory | |||
| Memory Capacity | 80GB HBM3 | 80GB HBM3 | 141GB HBM3e |
| Memory Bandwidth | 2.0TB/s | 3.35TB/s | 4.8TB/s |
| Memory Bus Width | 5120-bit | 6144-bit | |
| L2 Cache | 50MB | ||
| ECC Memory | Yes | ||
| Performance | |||
| FP64 | 26 TFLOPS | 34 TFLOPS | 34 TFLOPS |
| FP32 | 51 TFLOPS | 67 TFLOPS | 67 TFLOPS |
| TF32 Tensor | 756 TFLOPS | 989 TFLOPS | 989 TFLOPS |
| FP8 Tensor | 3,026 TFLOPS | 3,958 TFLOPS | 3,958 TFLOPS |
| LLM Inference | Baseline | Baseline | Up to 2X |
| Connectivity | |||
| NVLink | N/A | 18 links (900GB/s) | |
| PCIe | PCIe 5.0 x16 | ||
| Form Factor | Dual-slot FHFL | SXM5 Module | |
| Power & Thermal | |||
| TDP | 350W | 700W | |
| Cooling | Air or Liquid | Liquid Required | |
| Max Operating Temp | 83°C | ||
| Enterprise Features | |||
| MIG Support | Up to 7 instances | ||
| Confidential Computing | Yes | ||
| vGPU Support | Yes | ||
Ideal Use Cases
Hopper powers the most demanding enterprise AI workloads
LLM Training
Train large language models with the Transformer Engine and NVLink scaling to thousands of GPUs. Mature software ecosystem ensures reliable training runs.
AI Inference
Deploy models at scale with MIG partitioning. H200's 141GB enables serving larger models; H100 offers best price/performance for smaller models.
Large Models (H200)
Run Llama 2 70B, Mixtral 8x7B, and other large models that exceed 80GB. H200's 141GB eliminates memory constraints for memory-bound workloads.
Scientific HPC
34 TFLOPS FP64 performance for computational physics, chemistry, and climate modeling. ECC memory ensures data integrity.
Generative AI
Power text, image, video, and multimodal generation. Transformer Engine optimizes throughput for transformer-based architectures.
Multi-Tenant (H100 PCIe)
H100 PCIe's 350W TDP and air cooling enables deployment in standard servers for flexible, cost-effective inference infrastructure.
Architecture Comparison
How Hopper compares in NVIDIA's data center GPU lineup
H200 vs H100
- Memory: 141GB vs 80GB (+76%)
- Bandwidth: 4.8TB/s vs 3.35TB/s (+43%)
- LLM Inference: Up to 2X faster
- Compute: Same (67 TFLOPS FP32)
- Architecture: Same Hopper
- Best For: Large models vs General AI
Hopper vs Blackwell
- Memory: 80-141GB vs 192-288GB
- Training: Baseline vs 4X faster
- Inference: Baseline vs 30X faster
- Availability: Available now vs Newer
- Software: Mature vs Emerging
- Price: $20K-$30K vs $30K-$60K
Frequently Asked Questions
What is the difference between H100 and H200?
H200 is the memory-upgraded H100 with 141GB HBM3e (76% more than H100's 80GB HBM3) and 4.8TB/s bandwidth (43% faster). Both share the same Hopper architecture and compute capabilities. H200 excels at memory-bound workloads like LLM inference with up to 2X performance improvement for large models.
What is the difference between H100 SXM5 and PCIe?
H100 SXM5 delivers maximum performance with 700W TDP, 3.35TB/s bandwidth, 16,896 CUDA cores, and 18 NVLink connections (900GB/s). H100 PCIe offers easier deployment with 350W TDP, 2.0TB/s bandwidth, 14,592 CUDA cores, and standard PCIe 5.0. SXM5 requires liquid cooling; PCIe works in standard air-cooled servers.
How much does H100 and H200 cost?
H100 PCIe: $20,000-$25,000. H100 SXM5: $20,000-$25,000. H200 SXM: $24,000-$30,000. Complete 8-GPU DGX systems range from $250,000-$350,000. Contact SLYD for current pricing through our OEM partnerships.
What is MIG (Multi-Instance GPU)?
Multi-Instance GPU allows a single H100/H200 to be partitioned into up to 7 isolated GPU instances, each with dedicated compute, memory, and bandwidth. This enables multi-tenant deployments where different users or workloads share a single physical GPU securely.
Should I choose Hopper or Blackwell?
Choose Hopper (H100/H200) for proven reliability, mature software ecosystem, immediate availability, and competitive pricing. Choose Blackwell (B200/B300) if you need maximum performance with 4X faster training and 30X faster inference. Hopper is the safe choice; Blackwell is the performance leader.
Is H200 available in PCIe form factor?
No, H200 is only available in SXM form factor which requires specialized baseboards and liquid cooling. For PCIe deployments in standard servers, H100 PCIe remains the best option. Consider Blackwell B200 PCIe variants when they become available.
Deploy NVIDIA Hopper
Get enterprise H100 and H200 systems through our OEM partnerships with expert configuration and deployment support.