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 performance defines training efficiency: the A100 PCIe 40GB delivers 312 TFLOPS, over eight times the RTX 4070 SUPER's 35.5 TFLOPS, accelerating deep learning model training where half-precision tensor operations prevail. Inference benefits similarly from this tensor core advantage, enabling faster throughput for deployed models. The A100's FP32 at 19.5 TFLOPS trails the RTX 4070 SUPER's 35.5 TFLOPS, favoring the consumer GPU in graphics rendering or simulations reliant on single-precision math.
Memory specifications dictate workload feasibility: 1555 GB/s bandwidth and 40 GB capacity on the A100 support expansive batch sizes in transformer models, minimizing out-of-memory errors during LLM training. The RTX 4070 SUPER's 504 GB/s and 12 GB constrain it to smaller batches or distilled models, risking swaps that degrade speed. Power draw aligns closely at 250 W TDP for the A100 versus 220 W for the RTX 4070 SUPER, though the A100 yields superior throughput per watt in FP16-dominated tasks.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 PCIe 40GB
| 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 | ||
 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×) | |||
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 4070 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 40GB
Choose the A100 PCIe 40GB for production-scale AI pipelines requiring 40 GB VRAM and 312 TFLOPS FP16 performance. It outperforms in LLM training or inference on models exceeding 12 GB, with 1555 GB/s bandwidth enabling large batches. Cloud access from $0.60 per hour facilitates elastic scaling without hardware investment.
When to Choose the RTX 4070 SUPER
The RTX 4070 SUPER suits budget-conscious developers prototyping on desktops, leveraging 35.5 TFLOPS FP32 for Stable Diffusion or fine-tuning compact models within 12 GB VRAM. Its 220 W TDP fits standard workstations, and PCIe form factor simplifies local integration. Absence of cloud offers encourages outright purchase for persistent personal use.
Use Cases
The A100's 312 TFLOPS FP16 and 40 GB HBM2e VRAM enable training large LLMs with substantial batch sizes. The RTX 4070 SUPER's 12 GB and 35.5 TFLOPS FP16 limit it to smaller models.
A100 supports high-throughput inference on full-scale LLMs via 1555 GB/s bandwidth and 312 TFLOPS FP16. RTX 4070 SUPER manages only quantized or small variants within 12 GB.
RTX 4070 SUPER suffices for fine-tuning models under 12 GB at 35.5 TFLOPS FP32. A100 excels for parameter-heavy adapters needing 40 GB VRAM.
RTX 4070 SUPER generates images efficiently within 12 GB GDDR6X at 35.5 TFLOPS FP16. A100 overkill proves unnecessary for typical diffusion pipelines.
RTX 4070 SUPER's 35.5 TFLOPS FP32 outperforms A100's 19.5 TFLOPS for simulations. Lower 220 W TDP enhances desktop suitability.
Frequently Asked Questions
What is the VRAM difference between A100 PCIe 40GB and RTX 4070 SUPER?▾
The A100 PCIe 40GB has 40 GB HBM2e VRAM, while the RTX 4070 SUPER offers 12 GB GDDR6X. This gap allows A100 to load larger models without quantization. Memory bandwidth follows suit at 1555 GB/s versus 504 GB/s.
How does cloud pricing compare for these GPUs?▾
NVIDIA A100 PCIe 40GB rents from $0.60 per hour, averaging $1.85 per hour across 11 live offers. No live cloud offers exist for RTX 4070 SUPER. Local purchase suits the consumer GPU.
Which GPU wins in FP16 performance for AI training?▾
A100 PCIe 40GB achieves 312 TFLOPS FP16, exceeding RTX 4070 SUPER's 35.5 TFLOPS by over 8x. This tensor advantage speeds neural network training. FP32 reverses, with RTX at 35.5 TFLOPS over A100's 19.5 TFLOPS.
Is RTX 4070 SUPER viable for machine learning?▾
RTX 4070 SUPER handles fine-tuning and inference for models under 12 GB at 35.5 TFLOPS FP16/FP32. It falls short for large LLMs due to VRAM limits. Pair with quantization for broader use.
What are the TDP and form factor differences?▾
A100 PCIe 40GB draws 250 W in PCIe form, optimized for servers. RTX 4070 SUPER uses 220 W in consumer PCIe slots. Both support PCIe 4.0 interconnects.
When to pick A100 over RTX 4070 SUPER?▾
Select A100 for workloads needing 40 GB VRAM or 312 TFLOPS FP16, like LLM training. RTX 4070 SUPER fits prototyping with 12 GB and lower cost. Cloud pricing starts at $0.60/hr for A100.
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.