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's FP16 throughput of 312 TFLOPS vastly exceeds the RTX 4070's 29.1 TFLOPS, enabling faster AI model training where half-precision computations dominate, such as in deep learning frameworks like PyTorch or TensorFlow. Conversely, the RTX 4070 matches its FP16 with 29.1 TFLOPS in FP32, providing balanced performance for graphics rendering or single-precision scientific simulations, unlike the A100's 19.5 TFLOPS FP32 which prioritizes tensor core acceleration over raw FP32.
Memory specifications create the starkest real-world divide: the A100's 2039 GB/s bandwidth and 40 GB VRAM support large batch sizes in training massive models, preventing out-of-memory errors common on the RTX 4070's 504 GB/s and 12 GB limit. For inference, this allows the A100 to handle bigger models or higher concurrency without quantization, while the RTX 4070 suits smaller deployments but bottlenecks on data-heavy tasks. Power draw further differentiates them: 400W TDP for A100 demands robust cooling, versus 200W for efficient consumer use.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 SXM4 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 | ||
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
| 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 40GB
Choose the NVIDIA A100 SXM4 40GB for large-scale LLM training or scientific simulations requiring over 12 GB VRAM, as its 40 GB HBM2e and 2039 GB/s bandwidth accommodate massive datasets and batch sizes without splitting across GPUs. Its NVLink and InfiniBand interconnects excel in multi-GPU clusters for distributed training, where the RTX 4070 lacks comparable scaling. Cloud users facing $1.00 to $2.63 per hour costs benefit when throughput from 312 TFLOPS FP16 justifies the premium over consumer alternatives.
When to Choose the RTX 4070
The NVIDIA GeForce RTX 4070 fits budget prototyping, gaming-integrated AI, or small-scale inference at $0.07 to $0.14 per hour, leveraging its 29.1 TFLOPS FP32/FP16 balance for tasks under 12 GB VRAM. Its lower 200W TDP and PCIe simplicity suit solo developers or edge deployments without datacenter infrastructure. Newer Ada Lovelace architecture provides efficiency gains in Stable Diffusion or fine-tuning compact models, avoiding the A100's higher costs for non-enterprise needs.
Use Cases
The A100's 40 GB VRAM and 312 TFLOPS FP16 handle large language models without memory constraints, unlike the RTX 4070's 12 GB limit. Its high bandwidth of 2039 GB/s supports efficient large-batch training.
A100 accommodates full-precision large models with 40 GB HBM2e, enabling high concurrency via 2039 GB/s bandwidth. RTX 4070 requires quantization for models over 12 GB.
RTX 4070 suffices for small models under 12 GB at low cost, while A100 excels for parameter-heavy fine-tuning needing 40 GB VRAM. Choice depends on model size and budget.
RTX 4070's Ada architecture and 29.1 TFLOPS deliver fast image generation within 12 GB VRAM for consumer workflows. A100 overkill for typical Stable Diffusion at higher cost.
A100's 312 TFLOPS FP16 and NVLink scaling accelerate simulations with large datasets fitting 40 GB VRAM. RTX 4070's 12 GB restricts complex HPC tasks.
Frequently Asked Questions
What is the VRAM difference between A100 SXM4 40GB and RTX 4070?▾
The A100 SXM4 40GB has 40 GB HBM2e VRAM, while the RTX 4070 provides 12 GB GDDR6X. This gap affects handling of large AI models, with A100 supporting bigger batches.
How do FP16 performances compare?▾
A100 achieves 312 TFLOPS in FP16, far surpassing RTX 4070's 29.1 TFLOPS. This makes A100 ideal for accelerated AI training.
What are the cloud rental prices?▾
A100 SXM4 40GB starts at $1.00 per hour, averaging $2.63 across five offers. RTX 4070 begins at $0.07 per hour, averaging $0.14 across two offers.
Which has higher memory bandwidth?▾
A100 delivers 2039 GB/s, compared to RTX 4070's 504 GB/s. Higher bandwidth on A100 enables faster data throughput for memory-intensive tasks.
Is RTX 4070 newer than A100?▾
Yes, RTX 4070 uses 2023 Ada Lovelace architecture versus A100's 2020 Ampere. However, A100's datacenter optimizations outperform in AI workloads.
What is the TDP comparison?▾
A100 requires 400W TDP, while RTX 4070 uses 200W. Lower TDP makes RTX 4070 more power-efficient for lighter deployments.
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.