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
Compute performance favors the H100 decisively: its 1979 TFLOPS FP16 capability accelerates deep learning training, where half-precision dominates, far exceeding the RTX 4000 Ada's 26.7 TFLOPS. FP32 performance at 67 TFLOPS on H100 supports scientific simulations better than the 26.7 TFLOPS on RTX 4000 Ada. The H100's FP8 rating of 3958 TFLOPS enhances inference for quantized models.
Memory bandwidth of 3350 GB/s on the H100 enables larger batch sizes in training, minimizing data loading bottlenecks and boosting throughput for large datasets. The RTX 4000 Ada's 360 GB/s bandwidth constrains such workloads, limiting scalability. VRAM disparity, 80 to 94 GB versus 20 GB, determines model size feasibility: H100 handles billion-parameter LLMs, while RTX 4000 Ada suits smaller prototypes.
Power draw reflects intent: H100's 700W TDP suits dense clusters, RTX 4000 Ada's 130W fits edge or low-power setups.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100
| 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
| 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
Choose the H100 for enterprise-scale AI training and inference demanding 80 to 94 GB VRAM and 1979 TFLOPS FP16 performance. Its 3350 GB/s bandwidth supports massive batch sizes, and NVLink interconnect enables efficient multi-GPU configurations via SXM5 or PCIe forms. Cloud users benefit from 58 live offers averaging $3.16 per hour for high-throughput workloads like large LLMs.
When to Choose the RTX 4000 Ada
The RTX 4000 Ada excels in cost-sensitive prototyping or small-scale inference within 20 GB VRAM limits and 26.7 TFLOPS FP16. Its 130W TDP and PCIe form factor suit single-workstation clouds, with pricing from $0.09 per hour averaging $0.22 across 9 offers. Developers testing models under modest memory needs find it efficient.
Use Cases
H100's 80 to 94 GB HBM3 VRAM and 1979 TFLOPS FP16 handle massive models and large batches, exceeding RTX 4000 Ada's 20 GB GDDR6 capacity.
With 3958 TFLOPS FP8 and 3350 GB/s bandwidth, H100 delivers high-throughput serving; RTX 4000 Ada's 26.7 TFLOPS FP16 limits scale.
H100 supports larger datasets via 80 to 94 GB VRAM and 67 TFLOPS FP32, outperforming RTX 4000 Ada's constraints for efficient adaptation.
RTX 4000 Ada's 20 GB VRAM and 26.7 TFLOPS FP16 suffice for image generation at lower cost of $0.22 average per hour; H100 overkill for single instances.
H100's 67 TFLOPS FP32 and 3350 GB/s bandwidth accelerate simulations; RTX 4000 Ada's 26.7 TFLOPS falls short for complex computations.
Frequently Asked Questions
Which GPU has more VRAM: H100 or RTX 4000 Ada?▾
The H100 offers 80 to 94 GB HBM3 VRAM, significantly more than the RTX 4000 Ada's 20 GB GDDR6. This enables H100 to load larger models for training. RTX 4000 Ada suits smaller datasets.
How do cloud prices compare for H100 and RTX 4000 Ada?▾
H100 pricing starts at $0.80 per hour, averaging $3.16 across 58 offers. RTX 4000 Ada begins at $0.09 per hour, averaging $0.22 across 9 offers. Lower cost favors RTX 4000 Ada for light use.
What is the FP16 performance difference?▾
H100 achieves 1979 TFLOPS FP16, versus 26.7 TFLOPS on RTX 4000 Ada. This gap boosts H100 for AI training speed. Inference also benefits from H100's FP8 at 3958 TFLOPS.
Which has higher memory bandwidth?▾
H100 provides 3350 GB/s, compared to RTX 4000 Ada's 360 GB/s. Higher bandwidth on H100 allows bigger batch sizes in ML workflows. It reduces training time significantly.
Is RTX 4000 Ada more power efficient?▾
RTX 4000 Ada has a 130W TDP, much lower than H100's 700W. This suits low-power cloud instances or workstations. H100 prioritizes peak performance over efficiency.
Can RTX 4000 Ada handle LLM fine-tuning?▾
RTX 4000 Ada's 20 GB VRAM limits it to smaller LLMs, with 26.7 TFLOPS FP16 for moderate speed. H100's 80 to 94 GB excels for production fine-tuning. Choose based on model size.
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.