Specifications Compared
| Spec | A100 | QUADRO-RTX-4000 |
|---|---|---|
| TDP | 400W | 160W |
| VRAM | 40-80 GB | 8 GB |
| CUDA Cores | 6,912 | 2,304 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 288 |
| FP16 Performance | 312 TFLOPS | 7.1 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 7.1 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 416 GB/s |
Performance Analysis
The A100 SXM4 40GB's superior FP16 performance of 312 TFLOPS enables accelerated deep learning training and inference, processing tensor operations up to 44 times faster than the Quadro RTX 4000's 7.1 TFLOPS. This FP16 to FP32 ratio on the A100, at 312 TFLOPS versus 19.5 TFLOPS, supports mixed-precision training common in large models, reducing memory usage while maintaining accuracy. The Quadro's equal 7.1 TFLOPS in both FP16 and FP32 suits graphics rendering but limits scalability in AI pipelines requiring half-precision dominance.
Memory bandwidth profoundly impacts real-world throughput: the A100's 2039 GB/s allows batch sizes up to five times larger than the Quadro's 416 GB/s capacity, minimizing data bottlenecks in training loops for models exceeding 8 GB VRAM. For inference, the A100 handles high-concurrency requests with its 40 GB HBM2e, whereas the Quadro struggles with models over 8 GB GDDR6. Higher TDP of 400W on the A100 correlates with sustained peak performance in multi-GPU clusters via NVLink, unlike the Quadro's single PCIe limitation.
These specs translate to the A100 completing LLM fine-tuning epochs in minutes where the Quadro requires hours, emphasizing generational leaps in datacenter efficiency.
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 397GB Storage | Slovenia | $0.73/GPU/hr | 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×) |
Quadro RTX 4000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.56/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Canada | $0.56/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.56/GPU/hr $1.12/hr total (2×) | Available | ||
Paperspace | NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Amsterdam | $0.56/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | Canada | $0.56/GPU/hr $1.12/hr total (2×) | Available |
When to Choose the A100 SXM4 40GB
Select the NVIDIA A100 SXM4 40GB for AI model training and inference demanding over 8 GB VRAM, such as LLMs with billions of parameters. Its 312 TFLOPS FP16 and 2039 GB/s bandwidth enable large batch sizes and rapid iterations, ideal for research teams scaling on cloud instances starting at $1.00 per hour.
Datacenter deployments benefit from NVLink interconnects and 40 GB HBM2e, supporting multi-GPU synchronization unavailable on the Quadro RTX 4000.
When to Choose the Quadro RTX 4000
Opt for the NVIDIA Quadro RTX 4000 in budget-constrained visualization workflows like CAD or real-time rendering, where 8 GB GDDR6 and 7.1 TFLOPS suffice at $0.56 per hour. Lower 160W TDP fits edge workstations without cooling overhead.
Small-scale prototyping or non-AI tasks leverage its PCIe compatibility without needing datacenter interconnects.
Use Cases
The A100's 40 GB HBM2e VRAM and 312 TFLOPS FP16 handle massive datasets and large batch sizes, while the Quadro's 8 GB GDDR6 limits model scale.
High memory bandwidth of 2039 GB/s on the A100 supports concurrent high-volume requests for large models, exceeding the Quadro's 416 GB/s capacity.
A100's 19.5 TFLOPS FP32 and NVLink enable efficient multi-GPU fine-tuning of models over 8 GB, unavailable on the single PCIe Quadro.
Quadro RTX 4000's 7.1 TFLOPS suffices for standard image generation at low cost, but A100 accelerates high-resolution batches with 40 GB VRAM.
A100's 2039 GB/s bandwidth and 400W TDP sustain complex simulations, far beyond Quadro's 416 GB/s for memory-intensive HPC tasks.
Frequently Asked Questions
Which GPU has more VRAM: A100 SXM4 40GB or Quadro RTX 4000?▾
The A100 SXM4 40GB provides 40 GB HBM2e VRAM, five times the Quadro RTX 4000's 8 GB GDDR6. This enables larger models on the A100. Bandwidth reaches 2039 GB/s on A100 versus 416 GB/s on Quadro.
How do FP16 performances compare between A100 and Quadro RTX 4000?▾
A100 delivers 312 TFLOPS FP16, 44 times the Quadro RTX 4000's 7.1 TFLOPS. This accelerates AI training significantly. FP32 is 19.5 TFLOPS on A100 versus 7.1 TFLOPS on Quadro.
What are the cloud pricing differences for these GPUs?▾
A100 SXM4 40GB starts at $1.00 per hour with $2.63 average across five offers. Quadro RTX 4000 is $0.56 per hour average across five offers. A100 suits high-performance needs despite higher cost.
Which has higher power consumption: A100 or Quadro RTX 4000?▾
A100 SXM4 40GB has 400W TDP, more than double the Quadro RTX 4000's 160W. This supports peak sustained loads on A100. Quadro fits low-power setups.
Can Quadro RTX 4000 handle LLM training like A100?▾
Quadro RTX 4000's 8 GB VRAM limits it to small models, unlike A100's 40 GB for large LLMs. FP16 of 7.1 TFLOPS on Quadro pales against 312 TFLOPS on A100. Use Quadro for prototyping only.
What architectures power these GPUs?▾
A100 uses Ampere from 2020 for datacenter AI. Quadro RTX 4000 employs Turing from 2018 for workstations. A100's interconnects include NVLink, absent on Quadro.
Which is cheaper to rent, the A100 or the Quadro RTX 4000?▾
Cloud rental prices for both the A100 and Quadro RTX 4000 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 Quadro RTX 4000?▾
The A100 has 40 to 80 GB of HBM2e memory. The Quadro RTX 4000 has 8 GB of GDDR6 memory.
Can I find A100 and Quadro RTX 4000 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 Quadro RTX 4000?▾
The A100 uses the Ampere architecture (2020) while the Quadro RTX 4000 uses Turing (2018). The A100 delivers 43.9x the FP16 throughput and 4.9x the memory bandwidth of the Quadro RTX 4000.