Specifications Compared
| Spec | A100 | RTX-4000-ADA |
|---|---|---|
| TDP | 400W | 130W |
| VRAM | 40-80 GB | 20 GB |
| CUDA Cores | 6,912 | 6,144 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 192 |
| FP16 Performance | 312 TFLOPS | 26.7 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 26.7 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | 427 TOPS |
| Memory Bandwidth | 2,039 GB/s | 360 GB/s |
Performance Analysis
The A100's superior FP16 performance at 312 TFLOPS makes it ideal for AI training tasks using mixed precision, where most computations occur in half-precision to accelerate throughput on large datasets. In contrast, the RTX 4000 Ada's balanced 26.7 TFLOPS across FP16 and FP32 suits general-purpose rendering and inference on smaller models, but it falls short for training massive neural networks due to lower peak rates. The A100's FP32 at 19.5 TFLOPS still supports single-precision workloads effectively in HPC scenarios.
Memory bandwidth profoundly impacts real-world usage: A100's 2039 GB/s allows larger batch sizes in training, reducing overhead and enabling models up to 80 GB VRAM, whereas RTX 4000 Ada's 360 GB/s limits it to modest batches fitting within 20 GB. This results in A100 handling enterprise-scale inference with higher throughput, while RTX 4000 Ada excels in latency-sensitive, memory-constrained applications.
Power draw of 400W for A100 versus 130W for RTX 4000 Ada influences deployment: datacenters accommodate A100's higher TDP with NVLink interconnects for multi-GPU scaling, but RTX 4000 Ada fits edge or workstation setups with lower cooling needs.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 5672GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 769GB 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×) |
RTX 4000 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.26/GPU/hr | |||
Vast.ai | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 64 vCPU 42GB RAM 505GB Storage | Hungary | $0.40/GPU/hr | Available | ||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.44/GPU/hr | |||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 0 vCPU 0GB RAM | 🌍global | $0.57/GPU/hr |
When to Choose the A100
Choose the A100 for large language model training or scientific simulations requiring over 20 GB VRAM and high memory bandwidth of 2039 GB/s. Its 312 TFLOPS FP16 performance and NVLink support enable efficient multi-GPU clusters, ideal for data centers handling 80 GB models.
Enterprise inference on massive datasets also favors A100, where its 40-80 GB HBM2e capacity supports high batch sizes unavailable on RTX 4000 Ada.
When to Choose the RTX 4000 Ada
Opt for RTX 4000 Ada in budget-conscious prototyping or fine-tuning of models under 20 GB VRAM, leveraging its low $0.09 per hour starting price and 130W TDP for cost-effective cloud runs. The Ada Lovelace architecture provides modern features like improved ray tracing alongside balanced 26.7 TFLOPS FP16 and FP32.
Workstation tasks such as real-time visualization or small-scale inference benefit from its PCIe form factor and lower average pricing of $0.22 per hour across 9 offers.
Use Cases
A100's 40-80 GB HBM2e VRAM and 312 TFLOPS FP16 handle massive models and large batches, far exceeding RTX 4000 Ada's 20 GB GDDR6 and 26.7 TFLOPS.
High memory bandwidth of 2039 GB/s on A100 supports high-throughput inference on large models, while RTX 4000 Ada's 360 GB/s limits scale.
RTX 4000 Ada's 20 GB VRAM suffices for smaller fine-tuning datasets at lower cost of $0.09 per hour; A100 excels if exceeding 20 GB.
RTX 4000 Ada's 20 GB GDDR6 and 130W TDP fit image generation needs efficiently at $0.22 average per hour, matching Ada architecture advantages.
A100's 2039 GB/s bandwidth and NVLink interconnect accelerate simulations with large datasets, outperforming RTX 4000 Ada's 360 GB/s.
Frequently Asked Questions
What is the VRAM difference between A100 and RTX 4000 Ada?▾
A100 offers 40-80 GB HBM2e VRAM, enabling larger models than RTX 4000 Ada's 20 GB GDDR6. This gap affects handling of datasets over 20 GB. Bandwidth follows suit at 2039 GB/s versus 360 GB/s.
Which GPU has higher FP16 performance?▾
A100 achieves 312 TFLOPS in FP16, vastly superior to RTX 4000 Ada's 26.7 TFLOPS for AI training. FP32 rates are 19.5 TFLOPS on A100 versus 26.7 TFLOPS on RTX 4000 Ada. This favors A100 in mixed-precision workloads.
How do power consumption levels compare?▾
A100 draws 400W TDP, suited for datacenter cooling, while RTX 4000 Ada uses 130W for efficient workstations. Lower TDP reduces operational costs on RTX 4000 Ada. Form factors align with PCIe on both, plus SXM4 on A100.
What are the cloud pricing differences?▾
A100 starts at $0.60 per hour averaging $1.94 across 57 offers; RTX 4000 Ada from $0.09 per hour averaging $0.22 across 9 offers. Pricing reflects performance tiers. A100 suits high-end needs despite premium.
Which architecture is newer?▾
RTX 4000 Ada uses Ada Lovelace from 2023, postdating A100's Ampere of 2020. Newer architecture brings efficiency gains at 26.7 TFLOPS balanced compute. A100 retains leads in raw specs like 312 TFLOPS FP16.
Can these GPUs scale in multi-GPU setups?▾
A100 supports NVLink, PCIe 4.0, and InfiniBand for clustering; RTX 4000 Ada lacks specified interconnects beyond PCIe. This enables A100 in large-scale training. RTX 4000 Ada fits single-node tasks.
Which is cheaper to rent, the A100 or the RTX 4000 Ada?▾
Cloud rental prices for both the A100 and RTX 4000 Ada 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 4000 Ada?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 4000 Ada has 20 GB of GDDR6 memory.
Can I find A100 and RTX 4000 Ada 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 4000 Ada?▾
The A100 uses the Ampere architecture (2020) while the RTX 4000 Ada uses Ada Lovelace (2023). The A100 delivers 11.7x the FP16 throughput and 5.7x the memory bandwidth of the RTX 4000 Ada.