Specifications Compared
| Spec | H200 | RTX-2080 |
|---|---|---|
| TDP | 700W | 215W |
| VRAM | 141 GB | 8-11 GB |
| CUDA Cores | 16,896 | 2,944 |
| Memory Type | HBM3e | GDDR6 |
| Architecture | Hopper | Turing |
| Form Factors | SXM, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | NVLink |
| Tensor Cores | 528 | 368 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 10.1 TFLOPS |
| FP32 Performance | 67 TFLOPS | 10.1 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 4,800 GB/s | 616 GB/s |
Performance Analysis
The H200's FP16 performance of 1979 TFLOPS vastly outpaces the RTX 2080's 10.1 TFLOPS, accelerating neural network training by enabling larger batch sizes and faster iterations in deep learning tasks. FP32 at 67 TFLOPS for the H200 versus 10.1 TFLOPS on the RTX 2080 benefits simulation and rendering workloads requiring precise single-precision calculations. The FP16-to-FP32 delta on the H200 signals optimization for mixed-precision training, reducing memory usage while maintaining accuracy, a feature less pronounced on the Turing-based RTX 2080.
Memory bandwidth of 4800 GB/s on the H200 supports enormous batch sizes in transformer models, minimizing data transfer stalls that plague the RTX 2080's 616 GB/s limit, which caps effective throughput at smaller scales. In inference scenarios, the H200's 141 GB VRAM accommodates full-parameter loading for billion-scale LLMs, whereas the RTX 2080's 8-11 GB forces quantization or offloading, inflating latency. Power draw reflects efficiency trade-offs: 700W TDP for the H200 demands robust cooling, contrasting the RTX 2080's 215W suitability for edge deployments.
Real-world impacts include training times dropping from days to hours on the H200 for large models, while the RTX 2080 suits prototyping where absolute speed yields diminishing returns.
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 2080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA GeForce RTX 2080 Ti 11GB VRAM | 11GB | 32 vCPU 63GB RAM 1273GB Storage | Maryland | $0.13/GPU/hr | Available |
When to Choose the H200 SXM
The H200 excels in enterprise AI training and inference for models exceeding 70 billion parameters, leveraging 141 GB HBM3e VRAM and 4800 GB/s bandwidth to process datasets without splitting across GPUs. Datacenter users benefit from its 1979 TFLOPS FP16 and NVLink interconnects for multi-GPU scaling in HPC clusters.
Cloud deployments at $1.19 per hour justify selection for production workloads where throughput trumps cost, such as real-time generative AI services.
When to Choose the RTX 2080
The RTX 2080 fits budget-conscious hobbyists or developers prototyping small-scale ML models under 1 billion parameters, with 8-11 GB VRAM sufficient for fine-tuning and its $0.05 per hour pricing enabling low-risk experimentation.
Gaming and light creative tasks leverage its 10.1 TFLOPS FP32 and 215W TDP for desktop setups without datacenter infrastructure needs.
Use Cases
The H200's 141 GB VRAM and 1979 TFLOPS FP16 handle massive datasets and large batch sizes essential for training billion-parameter LLMs. The RTX 2080's 8-11 GB limits it to toy models.
H200 supports full-model loading with 141 GB HBM3e and 4800 GB/s bandwidth for low-latency serving. RTX 2080 requires heavy quantization due to VRAM constraints.
H200's 3958 TFLOPS FP8 accelerates efficient fine-tuning of large models without offloading. RTX 2080 struggles with memory for mid-sized adapters.
RTX 2080's 10.1 TFLOPS FP32 suffices for image generation at 512x512 resolutions on consumer budgets. H200 overkill for single-user creative tasks.
H200's 67 TFLOPS FP32 and NVLink enable parallel simulations on vast grids. RTX 2080's lower specs bottleneck complex physics or molecular dynamics.
Frequently Asked Questions
How much more VRAM does the H200 have than the RTX 2080?▾
The H200 provides 141 GB HBM3e VRAM, exceeding the RTX 2080's 8-11 GB GDDR6 by over 12 times. This enables loading complete large language models without partitioning. Bandwidth at 4800 GB/s further amplifies data handling versus 616 GB/s.
What is the FP16 performance difference between H200 and RTX 2080?▾
H200 delivers 1979 TFLOPS in FP16, approximately 196 times the RTX 2080's 10.1 TFLOPS. This gap accelerates AI training significantly. FP8 on H200 reaches 3958 TFLOPS, unavailable on the older card.
Which GPU is cheaper in the cloud?▾
RTX 2080 offers start from $0.05 per hour, averaging $0.07 across two providers, versus H200's $1.19 minimum and $3.83 average over 21 offers. Budget tasks favor the RTX 2080. Enterprise scale justifies H200 costs.
What are the power requirements for each GPU?▾
H200 has a 700W TDP suited for datacenter racks with advanced cooling. RTX 2080 draws 215W, ideal for standard desktops. This affects deployment: H200 needs infrastructure, RTX 2080 runs on consumer hardware.
Can the RTX 2080 handle modern AI workloads like the H200?▾
RTX 2080's 8-11 GB VRAM limits it to small models under quantization, unlike H200's 141 GB for native large-model runs. Performance at 10.1 TFLOPS FP16 pales against 1979 TFLOPS. Use RTX 2080 for prototyping only.
What interconnects do these GPUs support?▾
H200 uses NVLink, PCIe 5.0, and InfiniBand for high-speed clustering. RTX 2080 relies on NVLink and PCIe. H200 enables massive multi-GPU setups; RTX 2080 suits single-card or small-node use.
Which is cheaper to rent, the H200 or the RTX 2080?▾
Cloud rental prices for both the H200 and RTX 2080 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 2080?▾
The H200 has 141 GB of HBM3e memory. The RTX 2080 has 8 to 11 GB of GDDR6 memory.
Can I find H200 and RTX 2080 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 2080?▾
The H200 uses the Hopper architecture (2024) while the RTX 2080 uses Turing (2018). The H200 delivers 195.9x the FP16 throughput and 7.8x the memory bandwidth of the RTX 2080.