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 marks the starkest divide: the A100 achieves 312 TFLOPS versus 65.3 TFLOPS on the RTX 5000 Ada, accelerating neural network training where tensor cores exploit half-precision arithmetic. This translates to faster convergence in large-scale deep learning, often reducing training time by factors tied to the nearly 5x throughput advantage. Inference workloads similarly benefit from the A100's FP16 prowess for batched predictions on voluminous datasets. In FP32, the RTX 5000 Ada leads with 65.3 TFLOPS over the A100's 19.5 TFLOPS, suiting graphics rendering or simulations reliant on single-precision floats. Memory bandwidth reinforces the A100's edge at 2039 GB/s compared to 576 GB/s: higher rates support larger batch sizes in training, minimizing data starvation for models exceeding 32 GB VRAM capacity. The A100's 40 GB HBM2e sustains memory-intensive tasks longer than the RTX 5000 Ada's 32 GB GDDR6, though the latter's lower 250W TDP versus 400W aids dense deployments.
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 | 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 SXM4 40GB
The A100 SXM4 40GB stands out for large-scale AI training and HPC simulations requiring 40 GB HBM2e VRAM and 2039 GB/s bandwidth. Multi-GPU clusters leverage NVLink and InfiniBand for low-latency scaling, ideal for distributed training of models over 30 billion parameters. Its 312 TFLOPS FP16 performance handles memory-bound workloads efficiently.
When to Choose the RTX 5000 Ada Generation
The RTX 5000 Ada Generation fits cost-sensitive inference and fine-tuning with pricing from $0.25 per hour and 250W TDP. Balanced 65.3 TFLOPS across FP16 and FP32 supports visualization or smaller models within 32 GB GDDR6. Single-node PCIe setups benefit from its Ada Lovelace efficiency without datacenter interconnect needs.
Use Cases
A100's 312 TFLOPS FP16 and 2039 GB/s bandwidth manage massive models better than RTX 5000 Ada's 65.3 TFLOPS and 576 GB/s. NVLink scaling accelerates distributed runs.
A100's 40 GB VRAM and high bandwidth support larger batch inference versus RTX 5000 Ada's 32 GB limit. FP16 throughput at 312 TFLOPS yields lower latency.
RTX 5000 Ada's 65.3 TFLOPS FP32 and $0.25 per hour pricing suit smaller datasets, while A100's memory excels for parameter-heavy tuning.
RTX 5000 Ada's Ada Lovelace architecture and balanced FP32/FP16 at 65.3 TFLOPS optimize image generation efficiently. Lower 250W TDP reduces costs.
RTX 5000 Ada's 65.3 TFLOPS FP32 outperforms A100's 19.5 TFLOPS for simulations. PCIe form factor and $0.51 per hour average fit single-node analysis.
Frequently Asked Questions
What is the VRAM capacity of each GPU?▾
The A100 SXM4 40GB provides 40 GB HBM2e VRAM, while the RTX 5000 Ada offers 32 GB GDDR6. This difference impacts handling of large models, with A100 supporting bigger datasets. Bandwidth follows at 2039 GB/s for A100 versus 576 GB/s.
How do FP16 performances compare?▾
A100 delivers 312 TFLOPS FP16, far exceeding RTX 5000 Ada's 65.3 TFLOPS. This boosts AI training speed significantly. Inference also gains from the gap.
What are the current cloud prices?▾
A100 SXM4 40GB starts at $1.00 per hour, averaging $2.53 across six offers. RTX 5000 Ada begins at $0.25 per hour, averaging $0.51 over five offers. Prices reflect datacenter versus workstation roles.
Which has higher power consumption?▾
A100 requires 400W TDP, double the RTX 5000 Ada's 250W. This affects cooling and density in cloud instances. Lower TDP aids RTX for edge cases.
Can these GPUs scale in multi-GPU setups?▾
A100 supports NVLink, PCIe 4.0, and InfiniBand for efficient multi-GPU communication. RTX 5000 Ada relies solely on PCIe, limiting cluster performance. A100 suits distributed training.
What architectures power these GPUs?▾
A100 uses Ampere from 2020, optimized for datacenter compute. RTX 5000 Ada employs Ada Lovelace from 2023, enhancing ray tracing and efficiency. The generational shift improves RTX FP32 at 65.3 TFLOPS.
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.