Specifications Compared
| Spec | A100 | RTX-3060 |
|---|---|---|
| TDP | 400W | 170W |
| VRAM | 40-80 GB | 12 GB |
| CUDA Cores | 6,912 | 3,584 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Ampere |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 112 |
| FP16 Performance | 312 TFLOPS | 12.7 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 12.7 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 360 GB/s |
Performance Analysis
Compute capabilities define real-world applicability: A100's 312 TFLOPS FP16 vastly outpaces RTX 3060's 12.7 TFLOPS, accelerating deep learning training where half-precision dominates. The FP32 performance of 19.5 TFLOPS on A100 edges RTX 3060's 12.7 TFLOPS, benefiting simulations, yet RTX 3060's balanced FP16 and FP32 suits graphics and general inference equally. For training large neural networks, A100's tensor core optimizations reduce epochs significantly.
Memory bandwidth profoundly impacts batch sizes: A100's 2039 GB/s allows processing batches up to 80 GB VRAM capacity, enabling stable training of models like large language models without gradient accumulation hacks. RTX 3060's 360 GB/s and 12 GB VRAM constrain batches, increasing overhead for models exceeding 10 GB. Inference benefits similarly, with A100 supporting higher throughput for production serving.
Power efficiency varies by workload: A100's 400W TDP yields superior perf-per-watt in FP16-heavy tasks at 0.78 TFLOPS/W, while RTX 3060's 170W provides 0.075 TFLOPS/W FP16, better for low-power edge cases but inadequate for sustained high-load compute.
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 | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 128 vCPU 1024GB RAM 15200GB Storage | Virginia | $1.15/GPU/hr $9.20/hr total (8×) |
RTX 3060
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
Vast.ai | NVIDIA GeForce RTX 3060 12GB VRAM | 12GB | 36 vCPU 31GB RAM 862GB Storage | Texas | $0.23/GPU/hr | Available | ||
Vast.ai | 4×NVIDIA GeForce RTX 3060 12GB VRAM | 12GB | 128 vCPU 336GB RAM 1431GB Storage | Texas | $0.23/GPU/hr $0.90/hr total (4×) | Available | ||
Vast.ai | 2×NVIDIA GeForce RTX 3060 12GB VRAM | 12GB | 24 vCPU 55GB RAM 1940GB Storage | Texas | $0.23/GPU/hr $0.45/hr total (2×) | Available | ||
Vast.ai | 2×NVIDIA GeForce RTX 3060 12GB VRAM | 12GB | 64 vCPU 126GB RAM 3050GB Storage | Texas | $0.23/GPU/hr $0.45/hr total (2×) | Available |
When to Choose the A100 SXM4 80GB
Opt for A100 SXM4 80GB in large-scale AI training and inference requiring over 12 GB VRAM, such as LLMs with billions of parameters. Its 2039 GB/s bandwidth and 312 TFLOPS FP16 enable massive batch sizes and rapid iterations, with NVLink and InfiniBand facilitating multi-GPU clusters unavailable on RTX 3060.
Enterprise deployments demanding reliability and scalability favor A100, despite $1.46 per hour average cost, as 80 GB HBM2e handles datasets infeasible on consumer hardware.
When to Choose the RTX 3060
Select RTX 3060 for budget prototyping, small model inference, or gaming-integrated workflows at $0.07 per hour average. Its 12 GB GDDR6 suffices for fine-tuning under 10 GB or Stable Diffusion at 512x512 resolutions, with 170W TDP minimizing cloud power surcharges.
Hobbyists or startups testing ideas prioritize RTX 3060's 25x lower entry price of $0.03 per hour over A100's $0.79 per hour, as 12.7 TFLOPS FP16 handles lightweight tasks efficiently.
Use Cases
A100's 80 GB HBM2e VRAM and 312 TFLOPS FP16 support training models with billions of parameters at large batch sizes. RTX 3060's 12 GB limits it to tiny models.
A100's 2039 GB/s bandwidth delivers high throughput for production serving of large LLMs. RTX 3060 manages small models but bottlenecks on memory-intensive queries.
A100 handles full fine-tuning of models up to 80 GB with 19.5 TFLOPS FP32. RTX 3060 requires heavy quantization due to 12 GB VRAM.
RTX 3060's 12 GB GDDR6 runs standard Stable Diffusion at 12.7 TFLOPS FP16 effectively. A100 excels for high-resolution or batched generations but at higher cost.
A100's 19.5 TFLOPS FP32 and NVLink interconnects accelerate simulations across clusters. RTX 3060's single PCIe limits scalability.
Frequently Asked Questions
Which GPU has more VRAM, A100 SXM4 80GB or RTX 3060?▾
A100 SXM4 80GB provides 80 GB HBM2e VRAM, far exceeding RTX 3060's 12 GB GDDR6. This capacity allows A100 to load massive models without swapping. RTX 3060 suits smaller datasets under 12 GB.
What is the performance difference in FP16 between A100 and RTX 3060?▾
A100 achieves 312 TFLOPS in FP16, over 24 times RTX 3060's 12.7 TFLOPS. This gap accelerates AI training significantly on A100. RTX 3060 performs adequately for lighter inference.
How do cloud prices compare for A100 SXM4 80GB and RTX 3060?▾
A100 SXM4 80GB starts at $0.79 per hour, averaging $1.46 per hour across 22 offers. RTX 3060 begins at $0.03 per hour, averaging $0.07 per hour across 10 offers. The pricing reflects enterprise versus consumer positioning.
Which has higher memory bandwidth?▾
A100 delivers 2039 GB/s bandwidth with HBM2e, compared to RTX 3060's 360 GB/s GDDR6. Higher bandwidth on A100 supports larger batches in training. RTX 3060 handles modest data flows efficiently.
What are the TDP ratings?▾
A100 SXM4 80GB consumes 400W TDP, optimized for data centers. RTX 3060 uses 170W TDP, ideal for lower-power setups. A100's higher TDP enables sustained peak performance.
Are both GPUs on the Ampere architecture?▾
Yes, A100 launched in 2020 and RTX 3060 in 2021, both on Ampere. A100 targets compute with specialized features like NVLink. RTX 3060 emphasizes gaming with ray tracing cores.
Which is cheaper to rent, the A100 or the RTX 3060?▾
Cloud rental prices for both the A100 and RTX 3060 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 3060?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 3060 has 12 GB of GDDR6 memory.
Can I find A100 and RTX 3060 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 3060?▾
The A100 uses the Ampere architecture (2020) while the RTX 3060 uses Ampere (2021). The A100 delivers 24.6x the FP16 throughput and 5.7x the memory bandwidth of the RTX 3060.