NVIDIA H200 Server
NVIDIA H200 Server is a flagship GPU cloud server available from Immers Cloud. The H200 is NVIDIA's most powerful data center GPU, featuring 141 GB of HBM3e memory and massive compute throughput for large-scale AI training and inference.
Specifications
| Component !! Specification |
|---|
| GPU || NVIDIA H200 (Hopper architecture) |
| VRAM || 141 GB HBM3e |
| Memory Bandwidth || 4.8 TB/s |
| FP16 Performance || ~989 TFLOPS |
| FP8 Performance || ~1,979 TFLOPS |
| Interconnect || NVLink 4.0 (900 GB/s) |
| Starting Price || From $4.74/hr |
Performance
The NVIDIA H200 is the successor to the H100, with the same Hopper architecture but significantly upgraded memory:- 141 GB HBM3e vs 80 GB HBM2e on the H100 — 76% more VRAM
- 4.8 TB/s memory bandwidth vs 3.35 TB/s on H100 — 43% more bandwidth
- Identical compute units but memory improvements accelerate memory-bound workloads by 40–90%
- Training large language models (70B+ parameters)
- Fine-tuning foundation models (LLaMA, Mistral, GPT)
- Large-scale inference serving for production AI
- Scientific simulations with large memory requirements
- Multi-modal model training (vision + language)
- Research requiring state-of-the-art GPU hardware
- 141 GB HBM3e — largest GPU memory available
- 4.8 TB/s memory bandwidth eliminates memory bottlenecks
- Hopper architecture with FP8 tensor cores
- NVLink 4.0 for efficient multi-GPU scaling
- 40–90% faster than H100 on memory-bound workloads
- Highest per-hour cost at $4.74/hr
- Overkill for small models or inference-only workloads
- Limited availability due to high demand
- Requires expertise to fully utilize the hardware
- Cost adds up for sustained training runs
- NVIDIA H100 Server
- NVIDIA H100 NVL Server
- NVIDIA A100 Server
For LLM training, the extra VRAM means larger models can fit on a single GPU without model parallelism overhead. For inference, you can run larger batch sizes or serve bigger models without splitting across multiple GPUs.
Compared to the NVIDIA H100 Server ($3.83/hr), the H200 costs approximately 24% more per hour but delivers substantially better performance for memory-bound workloads, making it more cost-effective per token for large model inference.
Best Use Cases
Pros and Cons
Advantages
Limitations
Pricing
Available from Immers Cloud starting at $4.74/hr. Multi-GPU configurations available for distributed training. Monthly costs depend on usage patterns — a dedicated 24/7 instance runs approximately $3,413/month.Recommendation
The NVIDIA H200 Server is the right choice when you need the absolute fastest GPU available and your workload is memory-bandwidth bound. If you're training models with 70B+ parameters, running large-batch inference, or doing cutting-edge AI research, the H200's 141 GB HBM3e provides a clear advantage. For workloads that fit within 80 GB VRAM, the NVIDIA H100 Server offers similar compute at lower cost.See Also
Category:GPU Servers Category:AI Training Category:Data Center GPU