Specifications Compared
| Spec | H100 | RTX-3070 |
|---|---|---|
| TDP | 700W | 220W |
| VRAM | 80-94 GB | 8 GB |
| CUDA Cores | 16,896 | 5,888 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Ampere |
| Form Factors | SXM5, PCIe, 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 | 3,350 GB/s | 448 GB/s |
Performance Analysis
The compute disparity defines these GPUs: H100 SXM5 delivers 1979 TFLOPS in FP16 compared to 20.3 TFLOPS on RTX 3070 Ti, a nearly 100-fold advantage ideal for deep learning training where half-precision dominates. Its FP32 at 67 TFLOPS still outpaces the 3070 Ti's 20.3 TFLOPS, but the FP16 delta accelerates model training cycles dramatically, reducing time from days to hours for large neural networks. FP8 at 3958 TFLOPS on H100 further optimizes inference for quantized models. Memory bandwidth reveals another gap: 3350 GB/s on H100 SXM5 versus 448 GB/s on RTX 3070 Ti enables larger batch sizes, with H100 supporting 7 to 10 times more data throughput to minimize padding overhead in training. This sustains higher utilization in memory-bound tasks like transformer models. Power draw underscores efficiency differences: H100 SXM5 at 700W versus 220W on 3070 Ti, but H100's performance per watt excels in dense AI deployments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100 SXM5
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Hyperstack | 4×NVIDIA H100 PCIe 80GB VRAM | 80GB | 124 vCPU 720GB RAM 3300GB Storage | Canada | $1.90/GPU/hr $7.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA H100 PCIe 80GB VRAM | 80GB | 60 vCPU 360GB RAM 1600GB Storage | Canada | $1.90/GPU/hr $3.80/hr total (2×) | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.90/GPU/hr $15.20/hr total (8×) | Available | ||
Hyperstack | NVIDIA H100 PCIe 80GB VRAM | 80GB | 28 vCPU 180GB RAM 850GB Storage | Canada | $1.90/GPU/hr | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.95/GPU/hr $15.60/hr total (8×) | Available |
When to Choose the H100 SXM5
The H100 SXM5 suits enterprise AI training and inference for models exceeding 8 GB VRAM, such as large language models requiring 80 to 94 GB HBM3. Its 3350 GB/s bandwidth and 1979 TFLOPS FP16 enable massive batch sizes and rapid iterations, ideal for data centers with NVLink interconnects. Cloud users prioritize it for production-scale workloads despite $3.56 per hour average cost.
When to Choose the RTX 3070 Ti
The RTX 3070 Ti fits budget-conscious prototyping, small-scale inference, or gaming in the cloud at $0.06 per hour starting price. Its 8 GB GDDR6 handles lightweight fine-tuning or Stable Diffusion with 20.3 TFLOPS FP16, sufficient for hobbyists or tests not needing high VRAM. Low 220W TDP suits edge or multi-GPU consumer setups.
Use Cases
H100 SXM5's 80-94 GB HBM3 VRAM and 1979 TFLOPS FP16 support massive models; RTX 3070 Ti's 8 GB GDDR6 limits batch sizes severely.
3958 TFLOPS FP8 and 3350 GB/s bandwidth on H100 SXM5 enable high-throughput serving; 3070 Ti's 448 GB/s bottlenecks large queries.
Small datasets fit RTX 3070 Ti's 8 GB VRAM at low cost; H100 SXM5 accelerates with 67 TFLOPS FP32 for complex adapters.
RTX 3070 Ti's 20.3 TFLOPS FP16 generates images quickly on 8 GB VRAM; H100 SXM5 overkill for single-user creative tasks.
H100 SXM5's 3350 GB/s bandwidth and NVLink handle simulations; 3070 Ti's 448 GB/s suits basic analysis only.
Frequently Asked Questions
What is the VRAM difference between H100 SXM5 and RTX 3070 Ti?▾
H100 SXM5 provides 80 to 94 GB HBM3 VRAM, while RTX 3070 Ti offers 8 GB GDDR6. This gap limits 3070 Ti to small models but allows H100 to process datasets up to 10 times larger. Bandwidth follows suit at 3350 GB/s versus 448 GB/s.
How do cloud prices compare for these GPUs?▾
H100 SXM5 starts at $0.80 per hour with an average of $3.56 across 33 offers. RTX 3070 Ti begins at $0.06 per hour averaging $0.08 with 2 offers. The 40x price difference reflects H100's enterprise capabilities.
Is H100 SXM5 better for AI training than RTX 3070 Ti?▾
H100 SXM5 excels with 1979 TFLOPS FP16 versus 20.3 TFLOPS on 3070 Ti, speeding training by nearly 100 times. Its 700W TDP supports dense clusters. 3070 Ti suits prototypes only.
What are the power requirements?▾
H100 SXM5 has a 700W TDP for high-performance datacenter use. RTX 3070 Ti draws 220W, fitting consumer or light cloud instances. Efficiency favors H100 in flops per watt for AI.
Can RTX 3070 Ti handle large language models?▾
RTX 3070 Ti's 8 GB VRAM restricts it to models under 7B parameters without quantization. H100 SXM5's 80-94 GB supports 70B+ models natively. Use 3070 Ti for inference on tiny variants.
What architectures do they use?▾
H100 SXM5 employs Hopper from 2022 with FP8 support at 3958 TFLOPS. RTX 3070 Ti uses Ampere from 2020 with balanced 20.3 TFLOPS FP16 and FP32. Hopper optimizes modern AI tensor cores.
Which is cheaper to rent, the H100 or the RTX 3070?▾
Cloud rental prices for both the H100 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 H100 have compared to the RTX 3070?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 3070 has 8 GB of GDDR6 memory.
Can I find H100 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 H100 and the RTX 3070?▾
The H100 uses the Hopper architecture (2022) while the RTX 3070 uses Ampere (2020). The H100 delivers 97.5x the FP16 throughput and 7.5x the memory bandwidth of the RTX 3070.