Specifications Compared
| Spec | H100 | RTX-2060 |
|---|---|---|
| TDP | 700W | 160W |
| VRAM | 80-94 GB | 6-12 GB |
| CUDA Cores | 16,896 | 1,920 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Turing |
| 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 | 6.5 TFLOPS |
| FP32 Performance | 67 TFLOPS | 6.5 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 336 GB/s |
Performance Analysis
H100's FP16 performance of 1979 TFLOPS dwarfs RTX 2060's 6.5 TFLOPS: this enables training deep neural networks 300 times faster, as half-precision dominates AI pipelines. H100's FP32 at 67 TFLOPS still surpasses RTX 2060's 6.5 TFLOPS, but the FP16-to-FP32 ratio highlights H100's optimization for tensor cores in machine learning, versus RTX 2060's balanced Turing design for graphics.
Memory bandwidth defines scalability: H100's 3350 GB/s supports batch sizes 10 times larger than RTX 2060's 336 GB/s limit, cutting training epochs from days to hours for large models. In inference, H100's FP8 at 3958 TFLOPS processes billions more operations per second, ideal for real-time serving.
Power draw underscores trade-offs: H100's 700W TDP demands robust cooling, while RTX 2060's 160W suits edge deployments, though performance ceilings restrict it to modest tasks.
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 | |
|---|---|---|---|---|---|---|---|---|
 QuantaCloud Partner | H100 PCIe 32–1024+ GPUs · InfiniBand | ∞ | Custom configs | Multiple DCs | Reserved / cluster Get a quote in 24h | Available | ||
 CoreWeave | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 128 vCPU 0GB RAM 61440GB Storage | United States | $2.44/GPU/hr $19.51/hr total (8×) | |||
 Denvr | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 1024GB RAM 22800GB Storage | Virginia | $2.45/GPU/hr $19.60/hr total (8×) | |||
 Cirrascale | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 2048GB RAM 39738GB Storage | United States | $2.49/GPU/hr $19.92/hr total (8×) | |||
QuantaCloud | NVIDIA H100 PCIe 80GB VRAM | 80GB | 20 vCPU 128GB RAM 1250GB Storage | Midwest | $2.59/GPU/hr | Available | ||
QuantaCloud | 4×NVIDIA H100 PCIe 80GB VRAM | 80GB | 64 vCPU 512GB RAM 5000GB Storage | Midwest | $2.59/GPU/hr $10.36/hr total (4×) | Available |
QuantaCloud
Comparing H-series providers? We broker across all of them.
Most Hopper capacity is sold out through Q3 2026. If you need 16+ GPUs reserved or a cluster in the next 90 days, we quote remaining H-series or B300 inventory at partner rates — one quote, 24h turnaround.
When to Choose the H100 PCIe
Enterprise AI teams select the H100 PCIe for LLM training and inference: its 80-94 GB VRAM accommodates models like GPT variants that crash on RTX 2060's 6-12 GB. The 3350 GB/s bandwidth ensures massive datasets flow without bottlenecks, achieving FP16 speeds of 1979 TFLOPS.
Datacenter-scale scientific computing favors H100: NVLink and PCIe 5.0 interconnects enable multi-GPU clusters, unavailable on RTX 2060.
When to Choose the RTX 2060
Budget-conscious developers choose RTX 2060 for prototyping: at $0.02 per hour, it handles small-scale fine-tuning or Stable Diffusion with 6.5 TFLOPS FP16, avoiding H100's $1.25 per hour entry cost. Its 160W TDP fits low-power cloud instances.
Gaming or legacy graphics workloads suit RTX 2060: 6-12 GB GDDR6 suffices for real-time rendering, where H100's datacenter focus adds no value.
Use Cases
H100's 1979 TFLOPS FP16 and 80-94 GB VRAM handle massive parameter counts and large batches. RTX 2060's 6.5 TFLOPS and 6-12 GB VRAM cannot scale to full training runs.
H100's FP8 at 3958 TFLOPS and 3350 GB/s bandwidth enable high-throughput serving. RTX 2060 lacks FP8 and sufficient VRAM for production loads.
H100 supports parameter-efficient fine-tuning on 80-94 GB VRAM with 67 TFLOPS FP32. RTX 2060's 6-12 GB limits model sizes.
H100 generates images faster via 1979 TFLOPS FP16 for high-resolution tasks. RTX 2060 works for basic use but slows on larger batches due to 336 GB/s bandwidth.
H100's 67 TFLOPS FP32 and NVLink excel in simulations. RTX 2060's equal 6.5 TFLOPS FP16/FP32 suits only small datasets.
Frequently Asked Questions
Which GPU has more VRAM, H100 PCIe or RTX 2060?▾
H100 PCIe provides 80-94 GB HBM3 VRAM. RTX 2060 offers 6-12 GB GDDR6. This 10x difference allows H100 to load vast models.
What is the FP16 performance difference?▾
H100 achieves 1979 TFLOPS in FP16. RTX 2060 reaches 6.5 TFLOPS. H100 accelerates AI training by orders of magnitude.
How do cloud prices compare?▾
H100 PCIe starts at $1.25 per hour, averaging $2.70 across 18 offers. RTX 2060 begins at $0.02 per hour, averaging $0.04 across 2 offers.
What are the TDPs?▾
H100 PCIe consumes 700W. RTX 2060 uses 160W. Lower TDP makes RTX 2060 viable for power-sensitive setups.
Which has higher memory bandwidth?▾
H100 delivers 3350 GB/s. RTX 2060 provides 336 GB/s. H100 supports 10x larger batch sizes in training.
What architectures do they use?▾
H100 uses Hopper from 2022 with FP8 support at 3958 TFLOPS. RTX 2060 employs Turing from 2019.
Which is cheaper to rent, the H100 or the RTX 2060?▾
Cloud rental prices for both the H100 and RTX 2060 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 2060?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 2060 has 6 to 12 GB of GDDR6 memory.
Can I find H100 and RTX 2060 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 2060?▾
The H100 uses the Hopper architecture (2022) while the RTX 2060 uses Turing (2019). The H100 delivers 304.5x the FP16 throughput and 10.0x the memory bandwidth of the RTX 2060.