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
FP16 and FP32 capabilities define workload suitability: A100 PCIe 80GB reaches 312 TFLOPS FP16 versus 19.5 TFLOPS FP32, excelling in mixed-precision training and inference where tensor cores dominate deep learning. RTX 4070 Ti SUPER balances at 29.1 TFLOPS each, favoring FP32-heavy tasks like simulations or rendering over specialized AI acceleration.
Memory specs dictate practical limits. A100 PCIe 80GB's 80 GB HBM2e VRAM and 2039 GB/s bandwidth enable large models and batch sizes up to billions of parameters without errors. RTX 4070 Ti SUPER's 12 GB GDDR6X and 504 GB/s constrain it to smaller datasets, risking out-of-memory issues and smaller batches that extend runtimes.
Interconnects and power further differentiate: A100 supports NVLink, PCIe 4.0, InfiniBand for multi-GPU clusters at 400W TDP. RTX 4070 Ti SUPER relies on PCIe at 200W, suiting single-GPU, energy-efficient setups.
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 | 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 | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 126GB RAM 1114GB Storage | Czechia | $1.00/GPU/hr $2.00/hr total (2×) | Available | ||
Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 63GB RAM 646GB Storage | Czechia | $1.07/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 SUPER
| 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
NVIDIA A100 PCIe 80GB suits memory-intensive AI workloads: large language model training leverages 80 GB VRAM and 312 TFLOPS FP16 for massive batches. High-throughput inference and scientific computing benefit from 2039 GB/s bandwidth and NVLink scaling across nodes.
Enterprise teams select it for production pipelines where 10x cost over RTX 4070 Ti SUPER yields superior speed on datacenter-grade tasks.
When to Choose the RTX 4070 Ti SUPER
NVIDIA GeForce RTX 4070 Ti SUPER fits cost-optimized, lighter workloads. Fine-tuning small models or Stable Diffusion runs smoothly on 12 GB VRAM at $0.09 per hour starting rate. Its 29.1 TFLOPS FP32 and 200W TDP support prototyping, gaming, and low-batch inference without cluster needs.
Solo developers or startups choose it for 12x lower average pricing of $0.17 per hour when 80 GB capacity proves excessive.
Use Cases
A100 PCIe 80GB's 80 GB VRAM and 2039 GB/s bandwidth handle large models and batches exceeding RTX 4070 Ti SUPER's 12 GB limit. Its 312 TFLOPS FP16 accelerates training significantly.
High 312 TFLOPS FP16 on A100 delivers faster throughput for large models. RTX 4070 Ti SUPER's 12 GB VRAM restricts scale.
Smaller models fit both GPUs' VRAM. RTX 4070 Ti SUPER offers lower $0.09 per hour cost for quick iterations.
RTX 4070 Ti SUPER's Ada architecture and 29.1 TFLOPS FP32 excel in image generation at $0.17 per hour average. Lower TDP suits consumer tasks.
A100's NVLink, InfiniBand, and 80 GB VRAM support clustered HPC. Higher bandwidth aids data-heavy simulations.
Frequently Asked Questions
What are the cloud rental prices for A100 PCIe 80GB versus RTX 4070 Ti SUPER?▾
A100 PCIe 80GB starts from $0.89 per hour, averaging $2.08 across 28 offers. RTX 4070 Ti SUPER starts at $0.09 per hour, averaging $0.17 across 2 offers. The RTX provides roughly 12 times lower average cost.
Which GPU offers more VRAM?▾
A100 PCIe 80GB has 80 GB HBM2e VRAM. RTX 4070 Ti SUPER has 12 GB GDDR6X. A100 provides over six times the capacity for large models.
Does A100 outperform RTX 4070 Ti SUPER in FP16 for AI?▾
Yes. A100 achieves 312 TFLOPS FP16 versus 29.1 TFLOPS on RTX 4070 Ti SUPER. This gap speeds up training and inference by over 10 times in mixed precision.
What are the memory bandwidth figures?▾
A100 PCIe 80GB delivers 2039 GB/s. RTX 4070 Ti SUPER reaches 504 GB/s. A100's fourfold advantage supports larger batches.
Compare their power consumption TDPs.▾
A100 PCIe 80GB has 400W TDP. RTX 4070 Ti SUPER has 200W TDP. RTX uses half the power for lighter deployments.
Is RTX 4070 Ti SUPER sufficient for large model training?▾
No. Its 12 GB VRAM limits models far below A100's 80 GB threshold. Use RTX for small-scale tasks only.
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.