The NVIDIA H200 Tensor Core GPU represents a quantum leap in enterprise AI computing. Built on the cutting-edge Hopper architecture with 141GB HBM3e memory, it delivers unprecedented performance for the most demanding AI workloads.
Novita AI changes the game. We now offer H200 GPUs on-demand at $3.25/hour – delivering 19% savings over RunPod’s $3.99/hour pricing. This makes the world’s most advanced AI accelerator accessible for enterprise inference, large-scale model training, and cutting-edge research without prohibitive upfront costs.
Why H200 GPUs Dominate Enterprise AI
The H200’s game-changing advantage lies in its massive memory capacity. With 141GB of HBM3e memory and 4.8TB/s memory bandwidth, it delivers up to 1.9× faster inference performance on large language models like Llama 3.1 405B and Claude 3.5 compared to the H100.
This isn’t just an incremental improvement – it’s a fundamental shift in how enterprises can deploy AI.
Before H200: Enterprises faced an impossible choice between expensive multi-GPU H100 clusters for large models or accepting performance limitations with smaller configurations.
With H200: Single-GPU deployment of models that previously required complex distributed setups, dramatically reducing infrastructure complexity while boosting performance.
Hardware Specifications: H200 vs. H100 vs. A100
Memory Specifications Comparison
| Specification | H200 | H100 | A100 80GB |
|---|---|---|---|
| GPU Memory | 141GB HBM3e | 80GB HBM3 | 80GB HBM2e |
| Memory Bandwidth | 4.8TB/s | 3.35TB/s | 2.039TB/s (SXM) / 1.935TB/s (PCIe) |
| Memory Technology | HBM3e (Next-gen) | HBM3 | HBM2e |
| Memory Advantage | 76% more than H100 | Same as A100 | Baseline |
| Bandwidth Improvement | 43% over H100 | 64% over A100 | Baseline |
Compute Performance Specifications
| Precision Format | H200 SXM | H100 SXM | A100 80GB SXM |
|---|---|---|---|
| FP64 | 34 TFLOPS | 34 TFLOPS | 9.7 TFLOPS |
| FP64 Tensor Core | 67 TFLOPS | 67 TFLOPS | 19.5 TFLOPS |
| FP32 | 67 TFLOPS | 67 TFLOPS | 19.5 TFLOPS |
| TF32 Tensor Core | 989 TFLOPS | 989 TFLOPS | 156 TFLOPS |
| BFLOAT16 Tensor Core | 1,979 TFLOPS | 1,979 TFLOPS | 312 TFLOPS |
| FP16 Tensor Core | 1,979 TFLOPS | 1,979 TFLOPS | 312 TFLOPS |
| FP8 Tensor Core | 3,958 TFLOPS | 3,958 TFLOPS | Not supported |
| INT8 Tensor Core | 3,958 TOPS | 3,958 TOPS | 624 TOPS |
Form Factor and Power Specifications
| Specification | H200 | H100 | A100 |
|---|---|---|---|
| Form Factors | SXM, PCIe (H200 NVL) | SXM, PCIe | SXM, PCIe |
| Max TDP (SXM) | 700W | 700W | 400W (up to 500W CTS) |
| Max TDP (PCIe) | 600W (H200 NVL) | 350W | 300W |
| Cooling Requirements | Liquid cooling (SXM) | Liquid cooling (SXM) | Air/Liquid cooling |
Multi-Instance GPU (MIG) Capabilities
| GPU | MIG Instances | Memory per Instance | Use Cases |
|---|---|---|---|
| H200 SXM | Up to 7 MIGs | 18GB each | Large model serving |
| H200 NVL | Up to 7 MIGs | 16.5GB each | Enterprise deployment |
| H100 | Up to 7 MIGs | ~11GB each | Standard workloads |
| A100 | Up to 7 MIGs | 10GB each | Basic partitioning |
Interconnect and Networking
| Feature | H200 | H100 | A100 |
|---|---|---|---|
| NVLink Bandwidth | 900GB/s | 900GB/s | 600GB/s |
| PCIe Interface | Gen5 (128GB/s) | Gen4 (64GB/s) | Gen4 (64GB/s) |
| Multi-GPU Scaling | Up to 8 GPUs (HGX) | Up to 8 GPUs (HGX) | Up to 16 GPUs (HGX) |
| NVSwitch Support | Yes | Yes | Yes |
Enterprise-Grade Features Built for Production
Real Performance Impact in Enterprise AI Workloads
Large Language Model Inference: The 76% memory increase enables deployment of 100+ billion parameter models on single GPUs. Models requiring tensor parallelism across multiple H100s now run efficiently on one H200.
AI Model Training: Enhanced memory bandwidth accelerates gradient computations and parameter updates, while massive VRAM capacity supports larger batch sizes for improved training stability and faster convergence.
Research & Development: Fit larger models in memory, reduce development complexity, and accelerate iteration time. Experiment with architectures previously accessible only through expensive multi-GPU configurations.
Advanced Architecture Capabilities
5th-Generation Tensor Cores provide native support for FP8, FP16, BF16, and TF32 precision formats, with Transformer Engine optimization delivering automatic mixed-precision training for maximum efficiency without accuracy loss.
Multi-Instance GPU (MIG) partitions the H200 into up to 7 isolated instances, each with over 16GB memory – larger than many complete GPUs. Enable efficient resource sharing across multiple workloads while maintaining security isolation.
Enterprise Security includes confidential computing capabilities, ensuring sensitive AI models and data remain protected throughout the computation lifecycle in multi-tenant cloud environments.
Cost-Efficiency Breakthrough for Enterprise AI
The H200’s memory advantage translates directly into cost savings. Models that required 2×H100 GPUs for memory reasons now run on a single H200, delivering:
- Reduced infrastructure costs by up to 50%
- Simplified deployment architecture with fewer components
- Improved reliability through reduced inter-GPU communication
- Lower operational complexity and maintenance overhead
Why Novita AI Is Your Strategic H200 Partner
1. Unmatched Pricing Advantage
| Provider | H200 Hourly Rate | Your Savings |
|---|---|---|
| Novita AI | $3.25/hour | Baseline |
| RunPod | $3.99/hour | 19% savings |
Flexible Pricing Options:
Subscription: Annual subscriptions can save you hundreds of dollars while ensuring guaranteed resource availability and priority access
On-Demand: Pay-per-hour with no commitments, perfect for experimentation and variable workloads.
3. Ready-to-Use Templates and Custom Flexibility
Pre-configured Templates eliminate manual setup complexity with optimized configurations for popular models, including tested deployment parameters, environment variables, and container configurations. Get started instantly with models like DeepSeek, Llama, and other leading AI frameworks.
Custom Template Support provides advanced users with complete control over their deployment environment. Create specialized configurations with personalized deployment scripts, custom software stacks, and tailored optimization settings.
4. Global Deployment Network
Novita AI’s worldwide infrastructure spans 18 zones across multiple continents, providing comprehensive global coverage:
Get Started with H200 GPUs Today
Whether you’re deploying large language models for customer service automation, training proprietary AI models, running scientific simulations, or developing next-generation AI applications, the H200 on Novita AI provides the enterprise-grade performance and reliability your organization demands.
H200 GPU instances are available now. Visit our enterprise portal to launch your first instance and experience the future of enterprise AI computing.
Ready to get started? Contact our team or start your H200 instance now.
Frequently Asked Questions
H200 offers 76% more GPU memory (141GB vs 80GB) and 43% higher memory bandwidth, enabling single-GPU deployment of models that require multiple H100s while delivering up to 1.9× faster inference performance for large language models.
The H200 includes Multi-Instance GPU (MIG) for workload isolation, confidential computing for security, enterprise-grade reliability features, and compatibility with all major AI frameworks and enterpri
The NVIDIA H200 is a data center GPU built on Hopper architecture with 141GB HBM3e memory, designed for large-scale AI workloads. It offers the same compute as H100 but with 76% more memory for handling massive language models.
No, H200 uses Hopper architecture while Blackwell is NVIDIA’s newer architecture found in B200 GPUs. H200 is an enhanced Hopper with upgraded memory technology.
H200 GPUs cost $3.25/hour on Novita AI, which is 19% cheaper than RunPod’s $3.99/hour pricing.
Novita AI is an enterprise AI cloud platform that provides organizations with scalable access to cutting-edge GPU infrastructure, enabling rapid deployment and scaling of AI applications with enterprise-grade security and reliability.
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