Specifications Compared
| Spec | A100 | RTX-5000-ADA |
|---|---|---|
| TDP | 400W | 250W |
| VRAM | 40-80 GB | 32 GB |
| CUDA Cores | 6,912 | 12,800 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 400 |
| FP16 Performance | 312 TFLOPS | 65.3 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 65.3 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | 1,044 TOPS |
| Memory Bandwidth | 2,039 GB/s | 576 GB/s |
Performance Analysis
FP16 performance defines training advantages: the A100 reaches 312 TFLOPS, far exceeding the RTX 5000 Ada's 65.3 TFLOPS. This disparity accelerates matrix multiplications in deep learning, enabling faster iterations on large datasets.
FP32 capabilities shift priorities: RTX 5000 Ada matches 65.3 TFLOPS against A100's 19.5 TFLOPS. Such balance aids scientific simulations or rendering where single-precision precision matters without tensor core reliance.
Memory specs dictate practical limits: A100's 2039 GB/s bandwidth and 80 GB VRAM support expansive batch sizes in training, minimizing data transfer bottlenecks. RTX 5000 Ada's 576 GB/s and 32 GB VRAM constrain it to modest scales, though its 250W TDP offers efficiency over A100's 400W.
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 | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 63GB RAM 2826GB Storage | Slovenia | $0.73/GPU/hr | Available | ||
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 | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 63GB RAM 646GB Storage | Czechia | $1.07/GPU/hr | Available | ||
 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 5000 Ada Generation
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Chubbuck, Idaho | $0.55/GPU/hr | Available | ||
 RunPod | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 10 vCPU 83GB RAM | 🌍global | $0.83/GPU/hr |
When to Choose the A100 PCIe 80GB
Select the A100 PCIe 80GB for large-scale deep learning training. Its 80 GB HBM2e VRAM fits models beyond 32 GB, and 2039 GB/s bandwidth handles massive batches efficiently. NVLink, PCIe 4.0, and InfiniBand interconnects optimize multi-GPU clusters.
Datacenter deployments benefit from its 312 TFLOPS FP16 throughput, ideal for prolonged high-compute sessions despite 400W TDP.
When to Choose the RTX 5000 Ada Generation
Choose the RTX 5000 Ada Generation for cost-sensitive projects. Pricing starts at $0.25 per hour, averaging $0.51 per hour, versus A100's $0.89 per hour minimum.
Its 250W TDP enables denser cloud instances, and 65.3 TFLOPS FP32 suits inference or graphics workloads within 32 GB VRAM limits.
Use Cases
A100's 80 GB HBM2e VRAM and 2039 GB/s bandwidth manage enormous models and batches. RTX 5000 Ada's 32 GB GDDR6 falls short for large-scale training.
Many inference tasks fit RTX 5000 Ada's 32 GB VRAM at 65.3 TFLOPS FP16. A100's 312 TFLOPS provides faster throughput for high-volume serving.
Fine-tuning benefits from A100's 80 GB VRAM for parameter-heavy models. Its high bandwidth reduces latency during iterative updates.
RTX 5000 Ada's Ada Lovelace architecture and 65.3 TFLOPS FP32 excel in image generation. Lower 250W TDP and cost suit creative workflows.
A100's 312 TFLOPS FP16 accelerates simulations on large datasets. 80 GB VRAM handles complex grids without swapping.
Frequently Asked Questions
Which GPU has more VRAM?▾
The A100 PCIe 80GB offers 80 GB HBM2e VRAM. The RTX 5000 Ada Generation provides 32 GB GDDR6. This capacity edge makes A100 suitable for larger models.
What are the cloud pricing differences?▾
A100 PCIe 80GB starts at $0.89 per hour, averaging $2.06 per hour across 29 offers. RTX 5000 Ada begins at $0.25 per hour, averaging $0.51 per hour across 5 offers. RTX delivers better value for lighter tasks.
Which has higher FP16 performance?▾
A100 achieves 312 TFLOPS in FP16. RTX 5000 Ada reaches 65.3 TFLOPS. A100 dominates training workloads requiring half-precision compute.
How do memory bandwidths compare?▾
A100 provides 2039 GB/s bandwidth. RTX 5000 Ada offers 576 GB/s. Higher bandwidth on A100 supports bigger batch sizes in memory-intensive jobs.
What are the TDP ratings?▾
A100 consumes 400W TDP. RTX 5000 Ada uses 250W TDP. Lower power on RTX aids efficiency in multi-GPU or edge setups.
Which architecture is newer?▾
RTX 5000 Ada uses Ada Lovelace from 2023. A100 employs Ampere from 2020. Newer architecture brings RTX advancements in ray tracing and efficiency.
Which is cheaper to rent, the A100 or the RTX 5000 Ada?▾
Cloud rental prices for both the A100 and RTX 5000 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 5000 Ada?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 5000 Ada has 32 GB of GDDR6 memory.
Can I find A100 and RTX 5000 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 5000 Ada?▾
The A100 uses the Ampere architecture (2020) while the RTX 5000 Ada uses Ada Lovelace (2023). The A100 delivers 4.8x the FP16 throughput and 3.5x the memory bandwidth of the RTX 5000 Ada.