Specifications Compared
| Spec | A100 | RTX-2070 |
|---|---|---|
| TDP | 400W | 175W |
| VRAM | 40-80 GB | 8 GB |
| CUDA Cores | 6,912 | 2,304 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | NVLink |
| Tensor Cores | 432 | 288 |
| FP16 Performance | 312 TFLOPS | 7.5 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 7.5 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 448 GB/s |
Performance Analysis
The A100 PCIe 80GB excels in compute-intensive tasks due to its superior FP16 performance of 312 TFLOPS: this enables faster AI model training where half-precision arithmetic dominates, reducing training times significantly compared to the RTX 2070 SUPER's 9 TFLOPS FP16. Its FP32 performance of 19.5 TFLOPS also outperforms the 9 TFLOPS on the RTX 2070 SUPER, benefiting scientific simulations and general-purpose computing. Memory capacity is a key differentiator: 80 GB HBM2e on the A100 supports massive batch sizes and large language models without swapping, whereas 8 GB GDDR6 on the RTX 2070 SUPER limits workloads to smaller datasets. The 2039 GB/s bandwidth of the A100 PCIe 80GB accelerates data transfers for high-throughput inference, contrasting the RTX 2070 SUPER's 448 GB/s which bottlenecks large-scale operations. Power draw reflects intent: 400 W TDP for datacenter scale versus 215 W for desktop efficiency.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 PCIe 80GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 63GB RAM 2826GB Storage | Slovenia | $0.73/GPU/hr | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 794GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
 LeaderGPU | 8×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.90/GPU/hr $7.20/hr total (8×) | Available | ||
Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 63GB RAM 557GB Storage | Czechia | $1.00/GPU/hr | Available | ||
 Denvr | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 128 vCPU 1024GB RAM 15200GB Storage | Virginia | $1.15/GPU/hr $9.20/hr total (8×) |
When to Choose the A100 PCIe 80GB
Choose the A100 PCIe 80GB for enterprise AI training and inference where 80 GB VRAM handles models exceeding 8 GB, such as large LLMs. Its 312 TFLOPS FP16 and 2039 GB/s bandwidth enable scalable cloud deployments at $0.89 per hour starting price. High interconnect options like PCIe 4.0 suit multi-GPU clusters.
When to Choose the RTX 2070 SUPER
Select the RTX 2070 SUPER for budget gaming or lightweight local ML on desktops: its 8 GB GDDR6 suffices for small models and inference at lower 215 W TDP. Without cloud pricing, it appeals to one-time hardware purchases avoiding rental costs. It fits hobbyist Stable Diffusion runs without datacenter needs.
Use Cases
The A100 PCIe 80GB's 80 GB HBM2e VRAM and 312 TFLOPS FP16 support large batch sizes and rapid training of LLMs. The RTX 2070 SUPER's 8 GB limits model scale.
High 2039 GB/s bandwidth and 312 TFLOPS FP16 on the A100 enable high-throughput serving. The RTX 2070 SUPER struggles with memory for production loads.
A100 PCIe 80GB handles parameter-heavy fine-tuning with 19.5 TFLOPS FP32. RTX 2070 SUPER's 8 GB VRAM restricts dataset sizes.
RTX 2070 SUPER runs Stable Diffusion efficiently on 8 GB GDDR6 for local generation. A100 is overkill unless scaling to high resolutions.
A100's 19.5 TFLOPS FP32 and 80 GB VRAM accelerate simulations. RTX 2070 SUPER's 9 TFLOPS FP32 falls short for complex computations.
Frequently Asked Questions
What is the VRAM difference between NVIDIA A100 PCIe 80GB and RTX 2070 SUPER?▾
The A100 PCIe 80GB has 80 GB HBM2e VRAM, enabling large models. The RTX 2070 SUPER provides 8 GB GDDR6, suitable for smaller workloads. This 10x gap affects batch sizes in training.
How do FP16 performances compare?▾
A100 PCIe 80GB delivers 312 TFLOPS FP16 for fast AI acceleration. RTX 2070 SUPER offers 9 TFLOPS FP16. The A100 is over 34 times faster in half-precision tasks.
What are the cloud pricing options?▾
NVIDIA A100 PCIe 80GB starts at $0.89 per hour, averaging $2.08 per hour across 28 offers. RTX 2070 SUPER has no live cloud offers available.
Which has higher memory bandwidth?▾
A100 PCIe 80GB provides 2039 GB/s bandwidth for rapid data movement. RTX 2070 SUPER has 448 GB/s. This impacts large dataset processing.
Is RTX 2070 SUPER good for AI training?▾
RTX 2070 SUPER manages small-scale training with 9 TFLOPS FP32. It cannot compete with A100's 80 GB VRAM for production LLMs. Use it for prototyping.
What are the TDP ratings?▾
A100 PCIe 80GB requires 400 W TDP for datacenter use. RTX 2070 SUPER uses 215 W, ideal for desktops. Power needs align with deployment scale.
Which is cheaper to rent, the A100 or the RTX 2070?▾
Cloud rental prices for both the A100 and RTX 2070 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 A100 have compared to the RTX 2070?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 2070 has 8 GB of GDDR6 memory.
Can I find A100 and RTX 2070 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 A100 and the RTX 2070?▾
The A100 uses the Ampere architecture (2020) while the RTX 2070 uses Turing (2018). The A100 delivers 41.6x the FP16 throughput and 4.6x the memory bandwidth of the RTX 2070.