Specifications Compared
| Spec | H200 | RTX-5080 |
|---|---|---|
| TDP | 700W | 360W |
| VRAM | 141 GB | 16 GB |
| CUDA Cores | 16,896 | 10,752 |
| Memory Type | HBM3e | GDDR7 |
| Architecture | Hopper | Blackwell |
| Form Factors | SXM, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | 336 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 56.3 TFLOPS |
| FP32 Performance | 67 TFLOPS | 56.3 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | 900 TOPS |
| Memory Bandwidth | 4,800 GB/s | 960 GB/s |
Performance Analysis
The H200's 141 GB HBM3e VRAM enables handling massive models that exceed RTX 5080's 16 GB limit, allowing larger batch sizes in training without out-of-memory errors. Its 4800 GB/s bandwidth, five times RTX 5080's 960 GB/s, accelerates data transfers critical for memory-bound workloads like transformer inference.
H200's FP16 performance reaches 1979 TFLOPS with FP32 at 67 TFLOPS, emphasizing tensor core efficiency for AI training where mixed precision dominates; FP8 at 3958 TFLOPS further boosts quantized inference. RTX 5080 balances FP16 and FP32 at 56.3 TFLOPS each, suiting graphics rendering or general compute but lagging in scaled AI. The FP16 to FP32 delta on H200 signals specialization for deep learning over traditional rasterization.
Higher TDP of 700W on H200 supports sustained peak performance in multi-GPU setups via NVLink, while RTX 5080's 360W fits edge deployments but throttles under prolonged loads.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H200 SXM
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Atlanta | $1.99/GPU/hr | Available | ||
 Lambda Labs | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 64 vCPU 432GB RAM 4096GB Storage | Virginia | $2.29/GPU/hr | Available | ||
 Nebius | NVIDIA H200 SXM 141GB VRAM | 141GB | 16 vCPU 200GB RAM | 🌍Europe | $2.45/GPU/hr | |||
 CoreWeave | 8×NVIDIA H200 SXM 141GB VRAM | 141GB | 128 vCPU 0GB RAM 61440GB Storage | United States | $2.58/GPU/hr $20.64/hr total (8×) | |||
 Ori | 4×NVIDIA H200 SXM 141GB VRAM | 141GB | 96 vCPU 960GB RAM 12000GB Storage | London | $3.50/GPU/hr $14.00/hr total (4×) | Available |
RTX 5080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 5080 16GB VRAM | 16GB | 0 vCPU 0GB RAM | 🌍global | $0.59/GPU/hr |
When to Choose the H200 SXM
Enterprises running large language model training or inference select the H200 for its 141 GB VRAM, which accommodates models over 100 billion parameters without sharding. NVLink interconnect and 4800 GB/s bandwidth excel in multi-GPU clusters for scientific simulations demanding high throughput.
When to Choose the RTX 5080
Budget-conscious developers or gamers choose the RTX 5080 for tasks fitting within 16 GB VRAM, such as Stable Diffusion generation or fine-tuning small models, at $0.25 per hour. Its 360W TDP and PCIe form factor suit single-node workstations or portable cloud instances where cost averages $0.38 per hour.
Use Cases
H200's 141 GB VRAM and 1979 TFLOPS FP16 handle massive datasets and large batches essential for training billion-parameter models. RTX 5080's 16 GB limits scale severely.
The 4800 GB/s bandwidth and 3958 TFLOPS FP8 on H200 enable high-throughput serving of huge models. RTX 5080 struggles with memory constraints on production-scale inference.
H200 supports full-model fine-tuning with 141 GB VRAM for parameter-efficient methods on large LLMs. RTX 5080 suffices only for models under 16 GB.
RTX 5080's balanced 56.3 TFLOPS FP16/FP32 and lower $0.38 per hour cost fit image generation pipelines within 16 GB. H200 overkill for consumer creative tasks.
H200's 67 TFLOPS FP32 and NVLink excel in HPC simulations requiring high memory bandwidth of 4800 GB/s. RTX 5080 adequate for lighter serial computations.
Frequently Asked Questions
What is the VRAM difference between H200 and RTX 5080?▾
H200 provides 141 GB HBM3e VRAM, compared to RTX 5080's 16 GB GDDR7. This enables H200 for massive AI models while RTX 5080 targets smaller workloads.
How do cloud prices compare for H200 SXM vs RTX 5080?▾
H200 SXM starts at $1.19 per hour with $3.68 average across 24 offers. RTX 5080 starts at $0.25 per hour averaging $0.38 across 4 offers.
Which has higher FP16 performance: H200 or RTX 5080?▾
H200 delivers 1979 TFLOPS FP16, vastly exceeding RTX 5080's 56.3 TFLOPS. This gap favors H200 in AI training and inference.
What are the TDP ratings?▾
H200 has 700W TDP for sustained datacenter loads. RTX 5080 uses 360W, suitable for consumer and edge systems.
Can RTX 5080 handle LLM inference like H200?▾
RTX 5080's 16 GB VRAM limits it to small models, unlike H200's 141 GB for large-scale serving. Bandwidth of 960 GB/s on RTX 5080 trails H200's 4800 GB/s.
What architectures do they use?▾
H200 employs Hopper from 2024; RTX 5080 uses Blackwell from 2025. H200 focuses on datacenter AI, RTX 5080 on gaming and prosumer.
Which is cheaper to rent, the H200 or the RTX 5080?▾
Cloud rental prices for both the H200 and RTX 5080 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 H200 have compared to the RTX 5080?▾
The H200 has 141 GB of HBM3e memory. The RTX 5080 has 16 GB of GDDR7 memory.
Can I find H200 and RTX 5080 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 H200 and the RTX 5080?▾
The H200 uses the Hopper architecture (2024) while the RTX 5080 uses Blackwell (2025). The H200 delivers 35.2x the FP16 throughput and 5.0x the memory bandwidth of the RTX 5080.