Specifications Compared
| Spec | H100 | RTX-2080 |
|---|---|---|
| TDP | 700W | 215W |
| VRAM | 80-94 GB | 8-11 GB |
| CUDA Cores | 16,896 | 2,944 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Turing |
| Form Factors | SXM5, PCIe, 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 | 3,350 GB/s | 616 GB/s |
Performance Analysis
H100's FP16 performance reaches 1979 TFLOPS: this enables training large neural networks 196 times faster than RTX 2080's 10.1 TFLOPS. The FP32 disparity, 67 TFLOPS versus 10.1 TFLOPS, accelerates scientific simulations and rendering on H100. FP8 at 3958 TFLOPS on H100 further optimizes low-precision inference.
VRAM capacity defines batch size limits: H100's 80-94 GB HBM3 supports models exceeding 70 billion parameters, while RTX 2080's 8-11 GB GDDR6 restricts to small batches or low-resolution tasks. Memory bandwidth of 3350 GB/s on H100 versus 616 GB/s on RTX 2080 reduces data loading bottlenecks, improving throughput in memory-bound inference by over 5 times.
Power draw differs at 700W for H100 and 215W for RTX 2080, but cloud pricing absorbs this: H100's interconnects like PCIe 5.0 and InfiniBand enable scaling, absent in RTX 2080's basic NVLink.
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 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 H100 PCIe
Select the H100 PCIe for large-scale AI training: its 1979 TFLOPS FP16 and 80-94 GB VRAM handle billion-parameter LLMs without splitting. High bandwidth of 3350 GB/s supports massive batch sizes in inference pipelines.
Enterprise deployments favor H100: PCIe 5.0 and InfiniBand interconnects scale multi-GPU clusters efficiently, unlike RTX 2080 limitations.
When to Choose the RTX 2080
Opt for RTX 2080 in budget prototyping: at $0.05 per hour, it runs small models with 10.1 TFLOPS FP16 on 8-11 GB VRAM. Gaming or lightweight rendering leverages its PCIe form factor without high costs.
Hobbyists choose RTX 2080 for Stable Diffusion at low resolutions: 616 GB/s bandwidth suffices for non-enterprise tasks, saving over 95% versus H100 pricing.
Use Cases
H100's 1979 TFLOPS FP16 and 80-94 GB VRAM enable training models over 70B parameters without multi-GPU splits. RTX 2080's 10.1 TFLOPS and 8-11 GB VRAM cannot handle large datasets.
H100's 3958 TFLOPS FP8 and 3350 GB/s bandwidth serve high-throughput queries on massive models. RTX 2080's 616 GB/s limits batch sizes for production inference.
H100 accommodates full model fine-tuning with 80-94 GB VRAM for parameter-efficient methods. RTX 2080 suits only tiny models under 8 GB.
RTX 2080 generates 512x512 images at 10.1 TFLOPS FP16 for $0.05 per hour. H100 overkill for non-professional use.
H100's 67 TFLOPS FP32 excels in simulations needing high precision. RTX 2080's matching 10.1 TFLOPS FP32 falls short on scale.
Frequently Asked Questions
How much more VRAM does H100 have than RTX 2080?▾
H100 provides 80-94 GB HBM3 VRAM, exceeding RTX 2080's 8-11 GB GDDR6 by 8 to 11 times. This allows H100 to load models RTX 2080 cannot fit. Batch sizes grow proportionally in training.
What is the FP16 performance difference between H100 and RTX 2080?▾
H100 delivers 1979 TFLOPS FP16, 196 times RTX 2080's 10.1 TFLOPS. Training accelerates dramatically on H100. Inference benefits similarly in mixed precision.
Is H100 worth the higher cloud price over RTX 2080?▾
H100 averages $2.75 per hour versus RTX 2080's $0.07, but 1979 TFLOPS FP16 justifies it for AI tasks. Budget users stick to RTX 2080 for light loads.
Can RTX 2080 handle LLM inference?▾
RTX 2080 manages small LLMs up to 7B parameters on 8-11 GB VRAM at 10.1 TFLOPS FP16. Larger models require H100's 80-94 GB. Bandwidth limits throughput.
What architectures power these GPUs?▾
H100 uses Hopper from 2022 with PCIe 5.0 support. RTX 2080 runs Turing from 2018 on basic PCIe. H100 interconnects enable clustering.
Compare power consumption of H100 and RTX 2080.▾
H100 draws 700W TDP, RTX 2080 uses 215W. Cloud pricing includes power, so H100's $1.25 per hour reflects capability. Efficiency favors H100 per TFLOP.
Which is cheaper to rent, the H100 or the RTX 2080?▾
Cloud rental prices for both the H100 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 H100 have compared to the RTX 2080?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 2080 has 8 to 11 GB of GDDR6 memory.
Can I find H100 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 H100 and the RTX 2080?▾
The H100 uses the Hopper architecture (2022) while the RTX 2080 uses Turing (2018). The H100 delivers 195.9x the FP16 throughput and 5.4x the memory bandwidth of the RTX 2080.