Specifications Compared
| Spec | A100 | RTX-4070 |
|---|---|---|
| TDP | 400W | 200W |
| VRAM | 40-80 GB | 12 GB |
| CUDA Cores | 6,912 | 5,888 |
| Memory Type | HBM2e | GDDR6X |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 184 |
| FP16 Performance | 312 TFLOPS | 29.1 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 29.1 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | 466 TOPS |
| Memory Bandwidth | 2,039 GB/s | 504 GB/s |
Performance Analysis
The A100 PCIe 80GB demonstrates superior FP16 throughput at 312 TFLOPS compared to the RTX 4070 Ti's 29.1 TFLOPS: this gap benefits machine learning training where half-precision tensor operations dominate, accelerating model convergence. Conversely, FP32 performance stands at 19.5 TFLOPS on the A100 versus 29.1 TFLOPS on the RTX 4070 Ti, making the latter preferable for graphics rendering or single-precision scientific simulations.
Memory bandwidth marks a key differentiator: the A100's 2039 GB/s versus 504 GB/s on the RTX 4070 Ti supports larger batch sizes in deep learning, enabling efficient training of models exceeding 12 GB VRAM without swapping. This reduces overall training time and memory bottlenecks in inference pipelines. Power efficiency also varies, with the RTX 4070 Ti's 200W TDP halving the A100's 400W draw, suiting edge or cost-sensitive deployments.
In real-world terms, the A100 handles enterprise-scale AI, while the RTX 4070 Ti suffices for prototyping or inference on smaller datasets.
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 | 4×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 512GB RAM 7600GB Storage | Virginia | $1.15/GPU/hr $4.60/hr total (4×) |
RTX 4070 Ti
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the A100 PCIe 80GB
Select the A100 PCIe 80GB for large-scale LLM training or fine-tuning: its 80 GB HBM2e VRAM accommodates models like GPT-3 variants, unlike the RTX 4070 Ti's 12 GB limit. The 2039 GB/s bandwidth sustains high batch sizes, optimizing throughput in multi-GPU NVLink setups.
Datacenter environments with InfiniBand interconnects favor the A100 for scientific computing workloads demanding 312 TFLOPS FP16 performance.
When to Choose the RTX 4070 Ti
Choose the RTX 4070 Ti for cost-sensitive inference or Stable Diffusion tasks: at $0.08 per hour starting price, it delivers 29.1 TFLOPS FP32 for real-time rendering with 12 GB VRAM sufficing for most consumer models.
Gaming-adjacent AI prototyping benefits from its Ada Lovelace efficiency and 200W TDP, avoiding the A100's higher $0.89 per hour cost.
Use Cases
The A100's 80 GB HBM2e VRAM and 312 TFLOPS FP16 handle massive parameter counts and large batches. The RTX 4070 Ti's 12 GB limits it to smaller models.
RTX 4070 Ti offers 29.1 TFLOPS FP16 at $0.08 per hour for efficient small-to-medium model serving. A100's capacity exceeds typical inference needs.
A100's 2039 GB/s bandwidth supports high-batch fine-tuning on datasets fitting 80 GB VRAM. RTX 4070 Ti struggles with memory constraints.
RTX 4070 Ti's 29.1 TFLOPS FP32 and Ada architecture accelerate image generation at low $0.22 per hour average. 12 GB VRAM suffices for standard resolutions.
A100's NVLink and InfiniBand enable scalable simulations with 19.5 TFLOPS FP32. Higher bandwidth aids complex HPC workloads.
Frequently Asked Questions
What is the VRAM capacity of the A100 PCIe 80GB versus RTX 4070 Ti?▾
The A100 PCIe 80GB provides 80 GB HBM2e VRAM. The RTX 4070 Ti offers 12 GB GDDR6X VRAM. This difference impacts handling of large AI models.
How do memory bandwidths compare between these GPUs?▾
A100 PCIe 80GB achieves 2039 GB/s bandwidth. RTX 4070 Ti reaches 504 GB/s. Higher bandwidth on A100 supports larger batch sizes in training.
What are the cloud pricing differences?▾
A100 PCIe 80GB starts at $0.89 per hour, averaging $2.08 per hour across 28 offers. RTX 4070 Ti begins at $0.08 per hour, averaging $0.22 per hour across 5 offers.
Which GPU has better FP16 performance?▾
A100 PCIe 80GB delivers 312 TFLOPS FP16. RTX 4070 Ti provides 29.1 TFLOPS FP16. A100 excels in half-precision ML training.
What are the TDP ratings?▾
A100 PCIe 80GB has a 400W TDP. RTX 4070 Ti uses 200W TDP. Lower TDP on RTX 4070 Ti aids power-efficient deployments.
Which architecture do they use?▾
A100 PCIe 80GB employs Ampere from 2020. RTX 4070 Ti uses Ada Lovelace from 2023. Newer architecture brings efficiency gains to RTX 4070 Ti.
Which is cheaper to rent, the A100 or the RTX 4070?▾
Cloud rental prices for both the A100 and RTX 4070 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 4070?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find A100 and RTX 4070 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 4070?▾
The A100 uses the Ampere architecture (2020) while the RTX 4070 uses Ada Lovelace (2023). The A100 delivers 10.7x the FP16 throughput and 4.0x the memory bandwidth of the RTX 4070.