Specifications Compared
| Spec | H100 | RTX-4000-ADA |
|---|---|---|
| TDP | 700W | 130W |
| VRAM | 80-94 GB | 20 GB |
| CUDA Cores | 16,896 | 6,144 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Ada Lovelace |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | 192 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 26.7 TFLOPS |
| FP32 Performance | 67 TFLOPS | 26.7 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | 427 TOPS |
| Memory Bandwidth | 3,350 GB/s | 360 GB/s |
Performance Analysis
The H100 SXM5 vastly outperforms the RTX 4000 Ada in compute metrics: 1979 TFLOPS FP16 versus 26.7 TFLOPS, a 74-fold advantage ideal for AI training where half-precision accelerates matrix operations. FP32 performance shows 67 TFLOPS on H100 against 26.7 TFLOPS on RTX 4000 Ada, benefiting scientific simulations requiring single-precision accuracy.
Memory bandwidth defines workload feasibility: H100's 3350 GB/s enables massive batch sizes in model training, reducing iterations and time, while RTX 4000 Ada's 360 GB/s limits it to smaller batches prone to memory bottlenecks. For inference, H100's FP8 at 3958 TFLOPS supports ultra-fast serving of large language models, unavailable on RTX 4000 Ada.
Power draw underscores deployment differences: H100's 700W TDP suits data centers, contrasting RTX 4000 Ada's efficient 130W for edge or multi-GPU setups without high cooling needs.
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 |
RTX 4000 Ada Generation
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.26/GPU/hr | |||
 Vast.ai | 2×NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 64 vCPU 84GB RAM 1010GB Storage | Hungary | $0.40/GPU/hr $0.80/hr total (2×) | Available | ||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.44/GPU/hr | |||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 0 vCPU 0GB RAM | 🌍global | $0.57/GPU/hr |
When to Choose the H100 SXM5
Choose the H100 SXM5 for large-scale AI training and inference where 80 to 94 GB HBM3 VRAM accommodates models exceeding 20 GB. Its 1979 TFLOPS FP16 performance cuts training times dramatically compared to RTX 4000 Ada's 26.7 TFLOPS. High memory bandwidth of 3350 GB/s supports enormous batch sizes essential for efficient deep learning pipelines.
When to Choose the RTX 4000 Ada Generation
The RTX 4000 Ada Generation fits budget-limited projects like professional visualization or small-scale ML at $0.09 per hour starting price. Its 20 GB GDDR6 VRAM and 26.7 TFLOPS FP16 suffice for fine-tuning compact models or Stable Diffusion without H100's $0.80 per hour cost. Low 130W TDP enables deployment in standard workstations lacking datacenter infrastructure.
Use Cases
H100's 80-94 GB HBM3 VRAM and 1979 TFLOPS FP16 handle massive datasets and models. RTX 4000 Ada's 20 GB limits scale.
H100's 3958 TFLOPS FP8 and 3350 GB/s bandwidth enable high-throughput serving. RTX 4000 Ada struggles with large batches at 360 GB/s.
RTX 4000 Ada's 26.7 TFLOPS FP16 suits small models cost-effectively at $0.09/hr. H100 excels for parameter-heavy fine-tuning with 1979 TFLOPS.
RTX 4000 Ada's 20 GB VRAM and 26.7 TFLOPS FP16 generate images efficiently at low $0.27/hr average. H100 overkill for single-instance diffusion.
H100's 67 TFLOPS FP32 and 3350 GB/s bandwidth accelerate simulations. RTX 4000 Ada's 26.7 TFLOPS FP32 limits complex computations.
Frequently Asked Questions
What is the VRAM capacity of H100 SXM5 versus RTX 4000 Ada?▾
H100 SXM5 offers 80 to 94 GB HBM3 VRAM for large models. RTX 4000 Ada provides 20 GB GDDR6, suitable for smaller workloads.
How do FP16 performances compare?▾
H100 SXM5 achieves 1979 TFLOPS FP16 for rapid AI training. RTX 4000 Ada delivers 26.7 TFLOPS, adequate for lighter tasks.
What are the cloud pricing differences?▾
H100 SXM5 starts at $0.80 per hour, averaging $3.44 per hour across 35 offers. RTX 4000 Ada begins at $0.09 per hour, averaging $0.27 per hour across 10 offers.
Which has higher memory bandwidth?▾
H100 SXM5 provides 3350 GB/s, enabling large batch sizes. RTX 4000 Ada offers 360 GB/s for modest throughput.
What are the TDP ratings?▾
H100 SXM5 consumes 700W, designed for datacenters. RTX 4000 Ada uses 130W, ideal for workstations.
Which architecture is newer?▾
RTX 4000 Ada uses Ada Lovelace from 2023. H100 SXM5 employs Hopper from 2022, optimized for AI compute.
Which is cheaper to rent, the H100 or the RTX 4000 Ada?▾
Cloud rental prices for both the H100 and RTX 4000 Ada 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 4000 Ada?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 4000 Ada has 20 GB of GDDR6 memory.
Can I find H100 and RTX 4000 Ada 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 4000 Ada?▾
The H100 uses the Hopper architecture (2022) while the RTX 4000 Ada uses Ada Lovelace (2023). The H100 delivers 74.1x the FP16 throughput and 9.3x the memory bandwidth of the RTX 4000 Ada.