Specifications Compared
| Spec | H200 | RTX-3070 |
|---|---|---|
| TDP | 700W | 220W |
| VRAM | 141 GB | 8 GB |
| CUDA Cores | 16,896 | 5,888 |
| Memory Type | HBM3e | GDDR6 |
| Architecture | Hopper | Ampere |
| Form Factors | SXM, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | 184 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 20.3 TFLOPS |
| FP32 Performance | 67 TFLOPS | 20.3 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 4,800 GB/s | 448 GB/s |
Performance Analysis
The H200 NVL's FP16 performance of 1979 TFLOPS dwarfs the RTX 3070 Ti's 20.3 TFLOPS, accelerating deep learning training where half-precision dominates; its FP32 at 67 TFLOPS also exceeds the competitor's 20.3 TFLOPS for broader compute tasks. FP8 capability at 3958 TFLOPS on H200 NVL further boosts inference efficiency for quantized models, unavailable on the Ampere-based RTX 3070 Ti.
Memory specs dictate real-world viability: 141 GB HBM3e on H200 NVL supports enormous batch sizes and models exceeding 100 GB, while 8 GB GDDR6 on RTX 3070 Ti restricts to small-scale operations, often requiring gradient accumulation. Bandwidth of 4800 GB/s versus 448 GB/s prevents bottlenecks in data-heavy workflows, enabling H200 NVL to process large datasets 10x faster in memory-bound scenarios like transformer training.
TDP and interconnects amplify differences: 700W sustains peak throughput in clusters via NVLink and InfiniBand, contrasting the RTX 3070 Ti's 220W PCIe limit for single-node use.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H200 NVL
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Atlanta | $1.99/GPU/hr | Available | ||
 Lambda Labs | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 64 vCPU 432GB RAM 4096GB Storage | Virginia | $2.29/GPU/hr | Available | ||
 Nebius | NVIDIA H200 SXM 141GB VRAM | 141GB | 16 vCPU 200GB RAM | 🌍Europe | $2.45/GPU/hr | |||
 CoreWeave | 8×NVIDIA H200 SXM 141GB VRAM | 141GB | 128 vCPU 0GB RAM 61440GB Storage | United States | $2.58/GPU/hr $20.64/hr total (8×) | |||
 Ori | 4×NVIDIA H200 SXM 141GB VRAM | 141GB | 96 vCPU 960GB RAM 12000GB Storage | London | $3.50/GPU/hr $14.00/hr total (4×) | Available |
When to Choose the H200 NVL
Choose the H200 NVL for large-scale AI training or inference demanding over 8 GB VRAM, such as LLMs with billions of parameters fitting into its 141 GB HBM3e. Its 4800 GB/s bandwidth and 1979 TFLOPS FP16 excel in multi-GPU setups via NVLink, ideal for research labs or production serving at $0.50 per hour starting price.
High TDP of 700W and NVL form factor suit dense cloud clusters for scientific simulations requiring FP32 at 67 TFLOPS.
When to Choose the RTX 3070 Ti
The RTX 3070 Ti fits budget-conscious tasks like gaming, lightweight inference, or Stable Diffusion at 8 GB VRAM capacity, with cloud access from $0.06 per hour. Its 220W TDP and PCIe form factor enable easy desktop or small-instance cloud use without cluster complexity.
Select it for prototyping models under 8 GB or non-AI graphics where 20.3 TFLOPS FP16 suffices at average $0.08 per hour.
Use Cases
H200 NVL's 141 GB HBM3e VRAM accommodates massive models, with 1979 TFLOPS FP16 speeding convergence beyond RTX 3070 Ti's 8 GB limit.
3958 TFLOPS FP8 and 4800 GB/s bandwidth on H200 NVL handle high-throughput serving; 8 GB on RTX 3070 Ti restricts to tiny batches.
141 GB VRAM supports parameter-efficient fine-tuning on large LLMs; RTX 3070 Ti's 448 GB/s bandwidth bottlenecks even modest datasets.
RTX 3070 Ti's 8 GB GDDR6 suffices for image generation at 20.3 TFLOPS FP16, at $0.06 per hour versus H200 NVL's overkill for consumer scales.
H200 NVL excels at FP32 67 TFLOPS for simulations needing 141 GB; RTX 3070 Ti works for smaller problems at 20.3 TFLOPS and low $0.08 per hour cost.
Frequently Asked Questions
What is the VRAM difference between H200 NVL and RTX 3070 Ti?▾
H200 NVL offers 141 GB HBM3e VRAM, enabling large models. RTX 3070 Ti provides 8 GB GDDR6, suitable for smaller workloads. This 17x gap defines scalability.
How do FP16 performances compare?▾
H200 NVL achieves 1979 TFLOPS in FP16 for rapid AI training. RTX 3070 Ti delivers 20.3 TFLOPS, nearly 100x less. H200 NVL dominates deep learning.
What are the cloud pricing ranges?▾
H200 NVL starts at $0.50 per hour, averaging $2.39 across 4 offers. RTX 3070 Ti begins at $0.06 per hour, averaging $0.08 across 2 offers. Budget favors RTX.
Which has higher memory bandwidth?▾
H200 NVL provides 4800 GB/s, over 10x the RTX 3070 Ti's 448 GB/s. This boosts batch sizes in memory-intensive tasks. Datacenter use benefits most.
Can RTX 3070 Ti handle LLM inference?▾
RTX 3070 Ti manages small LLMs within 8 GB VRAM at 20.3 TFLOPS FP16. Larger models exceed limits, requiring H200 NVL's 141 GB.
Which is cheaper to rent, the H200 or the RTX 3070?▾
Cloud rental prices for both the H200 and RTX 3070 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the H200 have compared to the RTX 3070?▾
The H200 has 141 GB of HBM3e memory. The RTX 3070 has 8 GB of GDDR6 memory.
Can I find H200 and RTX 3070 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the H200 and the RTX 3070?▾
The H200 uses the Hopper architecture (2024) while the RTX 3070 uses Ampere (2020). The H200 delivers 97.5x the FP16 throughput and 10.7x the memory bandwidth of the RTX 3070.