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
Compute specifications highlight the A100 SXM4 80GB's dominance in AI tasks. Its 312 TFLOPS FP16 rate accelerates training and inference using half-precision formats, where models converge faster than on FP32 at 19.5 TFLOPS. The RTX 2070 SUPER equates FP16 and FP32 at approximately 9.1 TFLOPS, offering less benefit from precision reduction in modern deep learning pipelines.
Memory systems further separate the GPUs. The A100's 2039 GB/s bandwidth supports enormous batch sizes during training, minimizing overhead and enabling larger models within 80 GB VRAM. The RTX 2070 SUPER's 448 GB/s and 8 GB VRAM restrict batches, often causing memory errors in demanding workloads.
Interconnects and form factors suit distinct environments. NVLink and InfiniBand on the A100 enable multi-GPU clusters. PCIe on the RTX 2070 SUPER fits single-desktop use, though at lower overall throughput.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 SXM4 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 | 4×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 512GB RAM 7600GB Storage | Virginia | $1.15/GPU/hr $4.60/hr total (4×) |
When to Choose the A100 SXM4 80GB
Professionals select the A100 SXM4 80GB for large-scale AI training and inference. Its 80 GB VRAM accommodates massive LLMs or datasets, while 312 TFLOPS FP16 speeds iterations. Cloud pricing from $0.79 per hour across 22 offers provides scalable access without upfront hardware costs.
Data centers leverage its SXM4 form factor, 400 W TDP efficiency, and NVLink for distributed computing.
When to Choose the RTX 2070 SUPER
The RTX 2070 SUPER appeals to hobbyists and small teams for gaming, light inference, or prototyping. Its 8 GB VRAM and 9.1 TFLOPS FP32 handle modest models, and 215 W TDP integrates into standard PCs.
On-premise setups favor it due to no cloud rental fees, despite lacking live offers.
Use Cases
LLM training demands high VRAM and FP16 throughput: A100 SXM4 80GB's 80 GB HBM2e and 312 TFLOPS handle billion-parameter models efficiently. RTX 2070 SUPER's 8 GB limits scale.
Inference at production scale requires 2039 GB/s bandwidth for low latency: A100 excels here. RTX 2070 SUPER's 448 GB/s suits only small deployments.
Fine-tuning mid-sized models fits RTX 2070 SUPER's 8 GB VRAM and 9.1 TFLOPS. A100 SXM4 80GB accelerates larger efforts with 312 TFLOPS FP16.
Stable Diffusion image generation runs smoothly on RTX 2070 SUPER's 8 GB GDDR6 and 448 GB/s bandwidth. A100 overpowers simple creative tasks.
Simulations benefit from A100's 19.5 TFLOPS FP32 and NVLink interconnects for multi-GPU. RTX 2070 SUPER lacks scaling features.
Frequently Asked Questions
What is the VRAM difference between A100 SXM4 80GB and RTX 2070 SUPER?▾
The A100 SXM4 80GB has 80 GB HBM2e VRAM. The RTX 2070 SUPER provides 8 GB GDDR6. This allows A100 to process models ten times larger without splitting.
How do FP16 performances compare?▾
A100 SXM4 80GB reaches 312 TFLOPS FP16. RTX 2070 SUPER achieves approximately 9.1 TFLOPS. A100 offers over 34 times the half-precision compute for AI.
What are the cloud pricing details?▾
NVIDIA A100 SXM4 80GB starts at $0.79 per hour, averaging $1.46 per hour across 22 live offers. RTX 2070 SUPER has no live cloud offers available.
Which GPU has higher memory bandwidth?▾
A100 SXM4 80GB delivers 2039 GB/s. RTX 2070 SUPER provides 448 GB/s. Higher bandwidth on A100 supports larger training batches.
What are the TDP ratings?▾
A100 SXM4 80GB requires 400 W TDP. RTX 2070 SUPER uses 215 W. Lower TDP makes SUPER suitable for consumer power supplies.
Can RTX 2070 SUPER replace A100 for ML?▾
RTX 2070 SUPER manages small ML tasks with 9.1 TFLOPS FP32 and 8 GB VRAM. A100's 312 TFLOPS FP16 and 80 GB VRAM outperform for serious workloads.
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.