Specifications Compared
| Spec | A100 | QUADRO-RTX-8000 |
|---|---|---|
| TDP | 400W | 260W |
| VRAM | 40-80 GB | 48 GB |
| CUDA Cores | 6,912 | 4,608 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | NVLink |
| Tensor Cores | 432 | 576 |
| FP16 Performance | 312 TFLOPS | 16.3 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 16.3 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 672 GB/s |
Performance Analysis
The A100 demonstrates overwhelming superiority in FP16 performance at 312 TFLOPS compared to the Quadro RTX 8000's 16.3 TFLOPS. This gap accelerates mixed-precision training in deep learning, where FP16 tensor operations dominate, enabling faster iterations on large neural networks. FP32 performance also favors the A100 at 19.5 TFLOPS over the Quadro's 16.3 TFLOPS, benefiting single-precision scientific simulations or graphics rendering.
Memory bandwidth marks a stark contrast: the A100's 2039 GB/s versus 672 GB/s on the Quadro RTX 8000. Higher bandwidth sustains larger batch sizes in training and inference, reducing data transfer bottlenecks and improving throughput for memory-intensive tasks like transformer models. The A100's HBM2e memory outperforms GDDR6 in speed, further aiding high-resolution data processing.
Power consumption reflects their designs: 400W TDP for the A100 supports datacenter scaling, while the Quadro's 260W fits workstation constraints. Ampere's advancements over Turing yield better efficiency per watt in compute-heavy scenarios.
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×) |
When to Choose the A100 SXM4 40GB
Opt for the A100 SXM4 40GB in AI and machine learning workloads requiring peak FP16 throughput of 312 TFLOPS. It excels in training large language models or diffusion models where its 2039 GB/s bandwidth handles massive datasets efficiently. Cloud availability from $1.00 per hour makes it ideal for scalable, on-demand compute.
Datacenter deployments benefit from NVLink, PCIe 4.0, and InfiniBand for multi-GPU setups, outperforming the Quadro RTX 8000 in modern inference pipelines.
When to Choose the Quadro RTX 8000
Select the Quadro RTX 8000 for professional visualization or CAD applications in workstations leveraging its 48 GB GDDR6 VRAM. Its PCIe form factor and 260W TDP suit on-premises setups with lower power needs, avoiding datacenter overhead.
Legacy Turing-based software optimized for FP32 at 16.3 TFLOPS may run adequately here, especially without cloud pricing for alternatives.
Use Cases
The A100's 312 TFLOPS FP16 performance accelerates large model training far beyond the Quadro RTX 8000's 16.3 TFLOPS. Its 2039 GB/s bandwidth supports bigger batches for efficient convergence.
High memory bandwidth of 2039 GB/s on the A100 enables low-latency inference on large models. The Quadro RTX 8000's 672 GB/s limits throughput in production deployments.
A100's Ampere architecture and 19.5 TFLOPS FP32 handle fine-tuning precision needs better than the Quadro's Turing limits. Cloud access from $1.00 per hour adds flexibility.
The A100's 312 TFLOPS FP16 drives faster image generation than the Quadro RTX 8000's 16.3 TFLOPS. 40 GB HBM2e VRAM manages high-resolution outputs effectively.
Superior FP32 at 19.5 TFLOPS and NVLink interconnects make the A100 ideal for simulations. The Quadro RTX 8000's specs fall short for large-scale computations.
Frequently Asked Questions
What is the VRAM difference between A100 SXM4 40GB and Quadro RTX 8000?▾
The A100 SXM4 40GB has 40 GB HBM2e VRAM, while the Quadro RTX 8000 offers 48 GB GDDR6. HBM2e provides higher speed despite lower capacity, suiting bandwidth-heavy tasks.
How do FP16 performances compare?▾
A100 achieves 312 TFLOPS in FP16, dwarfing the Quadro RTX 8000's 16.3 TFLOPS. This benefits AI training with tensor cores.
What are the cloud prices for these GPUs?▾
A100 SXM4 40GB starts at $1.00 per hour, averaging $2.63 per hour across five offers. No live cloud offers exist for Quadro RTX 8000.
Which has higher memory bandwidth?▾
A100's 2039 GB/s exceeds the Quadro RTX 8000's 672 GB/s by over three times. This impacts batch sizes in ML workloads.
What are the TDPs?▾
A100 requires 400W TDP for datacenter use, compared to Quadro RTX 8000's 260W for workstations. Lower TDP aids power-constrained environments.
Which architecture is newer?▾
A100 uses Ampere from 2020, while Quadro RTX 8000 relies on Turing from 2018. Ampere delivers advancements in AI efficiency.
Which is cheaper to rent, the A100 or the Quadro RTX 8000?▾
Cloud rental prices for both the A100 and Quadro RTX 8000 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 8000?▾
The A100 has 40 to 80 GB of HBM2e memory. The Quadro RTX 8000 has 48 GB of GDDR6 memory.
Can I find A100 and Quadro RTX 8000 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 8000?▾
The A100 uses the Ampere architecture (2020) while the Quadro RTX 8000 uses Turing (2018). The A100 delivers 19.1x the FP16 throughput and 3.0x the memory bandwidth of the Quadro RTX 8000.