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's FP16 performance of 1979 TFLOPS vastly outpaces the RTX 4000 Ada's 26.7 TFLOPS, a factor of nearly 74 times, accelerating deep learning training where half-precision dominates. This gap shortens epochs for large models, while FP32 at 67 TFLOPS on H100 versus 26.7 TFLOPS supports precise scientific computations more efficiently. Inference benefits similarly, with H100 handling high-throughput serving.
Memory specs define scalability: H100's 3350 GB/s bandwidth and 80 to 94 GB VRAM enable massive batch sizes without swapping, ideal for training on datasets exceeding 20 GB. The RTX 4000 Ada's 360 GB/s and 20 GB limit it to smaller batches or models, risking out-of-memory issues in demanding scenarios. TDP reflects intent: 700W for sustained data center loads versus 130W for efficient workstations.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100 PCIe
| 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 | ||
 Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 928GB RAM 19200GB Storage | Dallas, Texas | $1.99/GPU/hr $15.92/hr total (8×) |
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 | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 64 vCPU 42GB RAM 505GB Storage | Hungary | $0.40/GPU/hr | 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 PCIe
Select the H100 PCIe for large-scale AI training, such as billion-parameter LLMs, where 1979 TFLOPS FP16 and 80 to 94 GB HBM3 VRAM handle enormous models and datasets. Its 3350 GB/s bandwidth supports batch sizes infeasible on lesser GPUs, reducing training time despite $2.59 per hour average cost.
When to Choose the RTX 4000 Ada Generation
The RTX 4000 Ada suits cost-sensitive workflows like visualization, small-scale inference, or Stable Diffusion, offering 26.7 TFLOPS FP16 at $0.27 per hour average. Its 130W TDP and PCIe form factor fit workstations or edge deployments without data center infrastructure.
Use Cases
H100's 1979 TFLOPS FP16 and 80 to 94 GB VRAM manage massive parameter counts and large batches. RTX 4000 Ada's 20 GB limits scale.
High throughput from 3958 TFLOPS FP8 and 3350 GB/s bandwidth serves production-scale queries. RTX 4000 Ada suffices only for tiny models.
H100 accelerates large models with 67 TFLOPS FP32; RTX 4000 Ada's 26.7 TFLOPS handles smaller ones cost-effectively at $0.27 per hour.
20 GB VRAM and 360 GB/s bandwidth generate images efficiently. H100's power is excessive for this at 700W TDP.
67 TFLOPS FP32 and high bandwidth tackle simulations needing precision. RTX 4000 Ada falls short for complex datasets.
Frequently Asked Questions
What is the VRAM capacity of H100 PCIe versus RTX 4000 Ada?▾
H100 PCIe provides 80 to 94 GB HBM3 VRAM, far exceeding the RTX 4000 Ada's 20 GB GDDR6. This enables H100 to load massive models without issues.
How do cloud prices compare for these GPUs?▾
H100 PCIe starts at $1.25 per hour, averaging $2.59 across 22 offers. RTX 4000 Ada begins at $0.09 per hour, averaging $0.27 across 10 offers.
What are the FP16 performance differences?▾
H100 achieves 1979 TFLOPS FP16, about 74 times the RTX 4000 Ada's 26.7 TFLOPS. This boosts training and inference speeds dramatically on H100.
Which has higher memory bandwidth?▾
H100's 3350 GB/s dwarfs RTX 4000 Ada's 360 GB/s, allowing larger batches and faster data access in AI workloads.
What are the TDP ratings?▾
H100 PCIe consumes 700W TDP for data center use, while RTX 4000 Ada uses 130W, suiting lower-power setups.
Is RTX 4000 Ada good for LLM training?▾
RTX 4000 Ada's 20 GB VRAM limits it to small LLMs; H100's 80 to 94 GB excels for production training.
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.