Specifications Compared
| Spec | A100 | RTX-2060 |
|---|---|---|
| TDP | 400W | 160W |
| VRAM | 40-80 GB | 6-12 GB |
| CUDA Cores | 6,912 | 1,920 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 240 |
| FP16 Performance | 312 TFLOPS | 6.5 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 6.5 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 336 GB/s |
Performance Analysis
The A100's FP16 performance of 312 TFLOPS vastly outpaces the RTX 2060's 6.5 TFLOPS, enabling faster AI model training where half-precision computations dominate. Its FP32 at 19.5 TFLOPS also exceeds the RTX 2060's 6.5 TFLOPS, benefiting single-precision scientific simulations. This delta means training large neural networks completes in minutes on A100 rather than hours on RTX 2060.
Memory bandwidth defines workload feasibility: A100's 2039 GB/s supports massive batch sizes and models fitting in 40-80 GB VRAM, preventing out-of-memory errors common with RTX 2060's 336 GB/s and 6-12 GB VRAM. Inference benefits similarly, as high bandwidth accelerates data throughput for real-time predictions.
Form factors and interconnects suit different scales. A100 supports SXM4, NVLink, PCIe 4.0, and InfiniBand for multi-GPU clusters, while RTX 2060 relies on PCIe alone. These traits position A100 for enterprise AI and RTX 2060 for solo, low-power tasks.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100
| 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 646GB Storage | Czechia | $1.07/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
Choose the A100 for large-scale AI training or inference requiring over 40 GB VRAM, such as LLMs with billions of parameters. Its 312 TFLOPS FP16 and 2039 GB/s bandwidth handle huge datasets and batch sizes efficiently, with NVLink enabling multi-GPU scaling unavailable on RTX 2060.
Datacenter workloads like scientific computing demand A100's 19.5 TFLOPS FP32 and 400W TDP tolerance in cloud clusters across 57 pricing offers.
When to Choose the RTX 2060
Opt for the RTX 2060 in budget-constrained scenarios like gaming or lightweight inference, where 6-12 GB VRAM and 6.5 TFLOPS suffice at $0.02 per hour. Its 160W TDP fits small-scale desktops or edge deployments without cluster needs.
Entry-level fine-tuning or Stable Diffusion runs favor RTX 2060's low average $0.04 per hour cost across available offers, avoiding A100's $1.92 premium for modest tasks.
Use Cases
A100's 40-80 GB HBM2e VRAM and 312 TFLOPS FP16 support massive models and datasets. RTX 2060's 6-12 GB GDDR6 limits scale.
2039 GB/s bandwidth on A100 enables high-throughput serving with large batches. RTX 2060's 336 GB/s suits only small models.
A100's 19.5 TFLOPS FP32 and high VRAM accelerate parameter-efficient tuning. RTX 2060 handles basic cases but slower at 6.5 TFLOPS.
RTX 2060's 6 GB GDDR6 runs standard generations at 6.5 TFLOPS FP16. A100 excels for high-res or batched outputs with 312 TFLOPS.
A100's 19.5 TFLOPS FP32 and InfiniBand suit simulations. RTX 2060's 6.5 TFLOPS limits complex computations.
Frequently Asked Questions
How much faster is A100 than RTX 2060 in FP16?▾
A100 achieves 312 TFLOPS FP16 versus RTX 2060's 6.5 TFLOPS, a 48x advantage for AI training. This translates to drastically reduced epochs in deep learning.
What is the VRAM difference between A100 and RTX 2060?▾
A100 provides 40-80 GB HBM2e, far exceeding RTX 2060's 6-12 GB GDDR6. Larger VRAM on A100 fits bigger models without swapping.
Is RTX 2060 cheaper than A100 in the cloud?▾
RTX 2060 starts at $0.02 per hour averaging $0.04 across 2 offers, versus A100's $0.45 minimum and $1.92 average over 57 offers. Savings suit light tasks.
Can RTX 2060 handle AI training like A100?▾
RTX 2060's 6.5 TFLOPS FP16 and 336 GB/s bandwidth limit it to small models. A100's 312 TFLOPS and 2039 GB/s target enterprise training.
What interconnects does A100 support?▾
A100 includes NVLink, PCIe 4.0, and InfiniBand for clustering. RTX 2060 uses only PCIe, restricting multi-GPU setups.
Which has higher power consumption?▾
A100 draws 400W TDP compared to RTX 2060's 160W. Higher TDP on A100 supports sustained peak performance in datacenters.
Which is cheaper to rent, the A100 or the RTX 2060?▾
Cloud rental prices for both the A100 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 A100 have compared to the RTX 2060?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 2060 has 6 to 12 GB of GDDR6 memory.
Can I find A100 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 A100 and the RTX 2060?▾
The A100 uses the Ampere architecture (2020) while the RTX 2060 uses Turing (2019). The A100 delivers 48.0x the FP16 throughput and 6.1x the memory bandwidth of the RTX 2060.