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 SXM4 80GB dominates in FP16 performance with 312 TFLOPS compared to the RTX 4070 Ti's 29.1 TFLOPS: this gap accelerates deep learning training by enabling mixed-precision workflows at over 10 times the speed. For FP32 tasks, the RTX 4070 Ti matches its FP16 at 29.1 TFLOPS against the A100's 19.5 TFLOPS, providing an edge in single-precision simulations or graphics rendering. Memory differences prove critical: the A100's 80 GB HBM2e VRAM and 2039 GB/s bandwidth support massive batch sizes for large models, whereas the RTX 4070 Ti's 12 GB GDDR6X and 504 GB/s limit it to smaller datasets and risk out-of-memory errors in training. In inference, high bandwidth on the A100 sustains throughput for production serving, while the RTX 4070 Ti suits lightweight deployments. Power efficiency favors the RTX 4070 Ti at 200 W versus 400 W, reducing costs in low-density setups.
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 | 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
| 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 SXM4 80GB
The A100 SXM4 80GB suits large-scale AI training and inference requiring over 12 GB VRAM. Its 80 GB HBM2e and 2039 GB/s bandwidth handle billion-parameter LLMs with large batches, preventing memory swaps. NVLink and InfiniBand enable multi-GPU scaling unavailable on the RTX 4070 Ti.
When to Choose the RTX 4070 Ti
The RTX 4070 Ti fits budget-conscious prototyping, fine-tuning small models, or inference on datasets under 12 GB. At $0.08 per hour from $0.22 average, it delivers 29.1 TFLOPS FP32 for scientific visualization or Stable Diffusion at one-fifth the A100's cost. Its Ada Lovelace architecture provides modern features for consumer-grade cloud tasks.
Use Cases
The A100's 80 GB VRAM and 312 TFLOPS FP16 support large models and batches without issues. The RTX 4070 Ti's 12 GB limits scale to smaller LLMs only.
High 2039 GB/s bandwidth on the A100 sustains high throughput for production serving. The RTX 4070 Ti works for small models but bottlenecks on larger ones.
A100's memory capacity fits full model loading during fine-tuning of large LLMs. RTX 4070 Ti requires heavy quantization for models over 12 GB.
RTX 4070 Ti's 29.1 TFLOPS and 12 GB VRAM generate images efficiently at low $0.22 per hour cost. A100 overkill for typical diffusion tasks.
A100's 312 TFLOPS FP16 accelerates simulations with tensor operations. Its interconnects scale across nodes better than RTX 4070 Ti.
Frequently Asked Questions
Which GPU has more VRAM: A100 SXM4 80GB or RTX 4070 Ti?▾
The A100 SXM4 80GB provides 80 GB HBM2e VRAM. The RTX 4070 Ti offers 12 GB GDDR6X, limiting it for memory-intensive tasks.
How do cloud prices compare for A100 SXM4 80GB and RTX 4070 Ti?▾
A100 SXM4 80GB pricing starts at $0.45 per hour, averaging $1.37 across 26 offers. RTX 4070 Ti begins at $0.08 per hour, averaging $0.22 across 5 offers.
Is the A100 faster than RTX 4070 Ti for AI training?▾
Yes, A100's 312 TFLOPS FP16 vastly exceeds RTX 4070 Ti's 29.1 TFLOPS, speeding training by over 10 times. Memory bandwidth of 2039 GB/s versus 504 GB/s further aids large batches.
What is the FP32 performance difference?▾
RTX 4070 Ti achieves 29.1 TFLOPS FP32, surpassing A100's 19.5 TFLOPS. This benefits FP32-heavy scientific computing on the consumer GPU.
Can RTX 4070 Ti handle large language models?▾
RTX 4070 Ti manages small LLMs under 12 GB with quantization. For full large models, A100's 80 GB VRAM is essential.
Which has higher power consumption?▾
A100 SXM4 80GB draws 400 W TDP. RTX 4070 Ti uses 200 W, offering better efficiency for light workloads.
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.