Specifications Compared
| Spec | H100 | RTX-4500-ADA |
|---|---|---|
| TDP | 700W | 210W |
| VRAM | 80-94 GB | 24 GB |
| CUDA Cores | 16,896 | 7,680 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Ada Lovelace |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | 240 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 39.6 TFLOPS |
| FP32 Performance | 67 TFLOPS | 39.6 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | 634 TOPS |
| Memory Bandwidth | 3,350 GB/s | 432 GB/s |
Performance Analysis
The H100's FP16 performance of 1979 TFLOPS dwarfs the RTX 4500 Ada's 39.6 TFLOPS, accelerating deep learning training where half-precision computations dominate. Its FP32 capability of 67 TFLOPS exceeds the RTX 4500 Ada's 39.6 TFLOPS, benefiting simulation and rendering tasks requiring full precision. FP8 support at 3958 TFLOPS on the H100 optimizes low-precision inference for production-scale LLMs. Memory bandwidth defines real-world limits: the H100's 3350 GB/s enables large batch sizes in training, reducing time for models exceeding 24 GB VRAM, while the RTX 4500 Ada's 432 GB/s constrains it to modest datasets. Higher TDP of 700W on H100 reflects datacenter cooling needs, versus 210W on RTX 4500 Ada for efficient single-node use. These differences translate to H100 completing epochs 50 times faster in FP16-heavy workloads.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100 NVL
| 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 4500 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX 4500 Ada 24GB VRAM | 24GB | 0 vCPU 0GB RAM | 🌍global | $0.74/GPU/hr |
When to Choose the H100 NVL
Select the H100 for large-scale AI training or inference where 80 to 94 GB HBM3 VRAM and 3350 GB/s bandwidth handle trillion-parameter models. Its NVLink interconnect and PCIe 5.0 support multi-GPU clusters for HPC environments. Cloud deployments at $1.40 to $2.89 per hour suit research teams prioritizing speed over cost.
When to Choose the RTX 4500 Ada
The RTX 4500 Ada fits development workflows with 24 GB GDDR6 VRAM adequate for fine-tuning mid-sized models or Stable Diffusion. Its 210W TDP integrates easily into workstations without extensive power infrastructure. At $0.34 to $0.51 per hour, it delivers strong value for prototyping and low-volume inference.
Use Cases
H100's 80-94 GB HBM3 VRAM and 1979 TFLOPS FP16 support massive models with large batch sizes via 3350 GB/s bandwidth.
3958 TFLOPS FP8 and high memory bandwidth deliver optimal high-throughput serving for deployed LLMs.
RTX 4500 Ada's 24 GB VRAM handles smaller models cost-effectively; H100 scales to larger ones.
39.6 TFLOPS FP16 and 24 GB VRAM generate images efficiently at $0.51 per hour average.
67 TFLOPS FP32 and NVLink interconnect accelerate complex simulations and multi-GPU parallelism.
Frequently Asked Questions
Which GPU has more VRAM?▾
The H100 provides 80 to 94 GB HBM3 VRAM, far exceeding the RTX 4500 Ada's 24 GB GDDR6. This enables H100 to load larger models without swapping. RTX 4500 Ada suffices for mid-sized workloads.
How do their FP16 performances compare?▾
H100 achieves 1979 TFLOPS FP16, over 50 times the RTX 4500 Ada's 39.6 TFLOPS. This gap accelerates AI training significantly. Inference also benefits from H100's FP8 at 3958 TFLOPS.
What is the memory bandwidth difference?▾
H100 offers 3350 GB/s, nearly eight times the RTX 4500 Ada's 432 GB/s. Higher bandwidth supports bigger batches in training. Lower bandwidth limits RTX 4500 Ada to smaller datasets.
Which is cheaper in the cloud?▾
RTX 4500 Ada starts at $0.34 per hour averaging $0.51 across three offers, versus H100 NVL at $1.40 per hour averaging $2.89 across nine. RTX 4500 Ada suits budgets. H100 justifies cost with performance.
What are their power requirements?▾
H100 has a 700W TDP for datacenter use, while RTX 4500 Ada draws 210W fitting workstations. Lower TDP reduces cooling needs for RTX 4500 Ada. H100 requires robust infrastructure.
Is H100 better for AI training?▾
Yes, H100's 1979 TFLOPS FP16 and 80-94 GB VRAM excel in LLM training. RTX 4500 Ada's 39.6 TFLOPS limits scale. Choose H100 for large models.
Which is cheaper to rent, the H100 or the RTX 4500 Ada?▾
Cloud rental prices for both the H100 and RTX 4500 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 4500 Ada?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 4500 Ada has 24 GB of GDDR6 memory.
Can I find H100 and RTX 4500 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 4500 Ada?▾
The H100 uses the Hopper architecture (2022) while the RTX 4500 Ada uses Ada Lovelace (2023). The H100 delivers 50.0x the FP16 throughput and 7.8x the memory bandwidth of the RTX 4500 Ada.