Specifications Compared
| Spec | QUADRO-RTX-8000 | V100 |
|---|---|---|
| TDP | 260W | 300W |
| VRAM | 48 GB | 16-32 GB |
| CUDA Cores | 4,608 | 5,120 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Turing | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink | NVLink, PCIe 3.0 |
| Tensor Cores | 576 | 640 |
| FP16 Performance | 16.3 TFLOPS | 125 TFLOPS |
| FP32 Performance | 16.3 TFLOPS | 15.7 TFLOPS |
| Memory Bandwidth | 672 GB/s | 900 GB/s |
Performance Analysis
The V100 demonstrates superior FP16 performance at 125 TFLOPS compared to the Quadro RTX 8000's 16.3 TFLOPS, enabling faster mixed-precision training for deep learning models. This delta means training large neural networks completes up to eight times quicker on the V100, as FP16 accelerates forward and backward passes without significant accuracy loss. The Quadro RTX 8000's equal FP16 and FP32 at 16.3 TFLOPS each better suits FP32-dominant inference or simulations where full precision matters.
Memory bandwidth plays a critical role: the V100's 900 GB/s supports larger batch sizes in memory-bound workloads like transformer training, reducing overhead from data transfers. The Quadro RTX 8000's 672 GB/s and 48 GB VRAM handle bigger models in inference scenarios, fitting datasets that exceed the V100's 32 GB maximum. Higher TDP on the V100 at 300W versus 260W reflects its datacenter optimization, potentially increasing cooling needs in dense clusters.
Real-world implications favor the V100 for throughput-oriented AI pipelines, while the Quadro RTX 8000 excels in VRAM-intensive tasks with balanced compute.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
V100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Texas | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | New York City | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Texas | $0.29/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | New York City | $0.29/GPU/hr | Available | ||
 Lambda Labs | 8×NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 88 vCPU 448GB RAM 6041GB Storage | Texas | $0.79/GPU/hr $6.32/hr total (8×) | Available |
When to Choose the Quadro RTX 8000
The Quadro RTX 8000 stands out for workloads requiring extensive VRAM, such as rendering massive datasets or running inference on models exceeding 32 GB. Its 48 GB GDDR6 capacity accommodates larger batch sizes or higher resolutions in professional visualization and CAD simulations. Balanced FP16 and FP32 at 16.3 TFLOPS each make it ideal for FP32-heavy scientific simulations where precision trumps half-precision speed.
PCIe form factor and NVLink support suit workstation multi-GPU configurations without datacenter infrastructure.
When to Choose the V100
The V100 proves superior for AI training tasks leveraging its 125 TFLOPS FP16 performance, drastically reducing epochs for large-scale models. Availability in cloud with pricing from $0.10 per hour across 72 offers makes it economical for bursty workloads. Higher 900 GB/s bandwidth enables efficient handling of memory-intensive operations like gradient computations.
SXM2 and PCIe options with NVLink and PCIe 3.0 interconnects fit scalable datacenter environments.
Use Cases
V100's 125 TFLOPS FP16 outperforms Quadro RTX 8000's 16.3 TFLOPS, speeding up mixed-precision training of large language models. Higher 900 GB/s bandwidth supports bigger batches.
Quadro RTX 8000's 48 GB VRAM handles larger models than V100's 32 GB maximum, enabling bigger inference batches. Balanced 16.3 TFLOPS FP32 suits precision needs.
V100's superior 125 TFLOPS FP16 accelerates fine-tuning iterations compared to 16.3 TFLOPS on Quadro RTX 8000. Cloud pricing from $0.10 per hour adds cost efficiency.
Quadro RTX 8000's 48 GB VRAM and Turing architecture manage high-resolution image generation better than V100's 32 GB limit. Equal FP16/FP32 at 16.3 TFLOPS aids diffusion steps.
V100 excels in FP16-heavy simulations at 125 TFLOPS, while Quadro RTX 8000's 48 GB VRAM fits large datasets. Choice depends on precision versus memory needs.
Frequently Asked Questions
Which GPU has more VRAM?▾
The Quadro RTX 8000 provides 48 GB GDDR6 VRAM, exceeding the V100's 16-32 GB HBM2. This makes the Quadro RTX 8000 better for memory-intensive inference. V100 prioritizes bandwidth at 900 GB/s over capacity.
What is the FP16 performance difference?▾
V100 delivers 125 TFLOPS FP16, vastly superior to Quadro RTX 8000's 16.3 TFLOPS. This gap favors V100 for half-precision training tasks. Quadro RTX 8000 matches its FP32 at 16.3 TFLOPS.
Which has higher memory bandwidth?▾
V100 offers 900 GB/s bandwidth from HBM2, outpacing Quadro RTX 8000's 672 GB/s GDDR6. Higher bandwidth on V100 supports larger batch sizes in training. It aids data-heavy workloads significantly.
What are the power requirements?▾
V100 has a 300W TDP, higher than Quadro RTX 8000's 260W. This reflects V100's datacenter focus with more compute. Quadro RTX 8000 suits power-constrained workstations.
Is cloud pricing available for these GPUs?▾
V100 has 72 live cloud offers from $0.10 per hour, averaging $0.94 per hour. Quadro RTX 8000 currently has no live offers. V100 provides better rental accessibility.
What interconnects do they support?▾
Both feature NVLink; V100 adds PCIe 3.0. Quadro RTX 8000 uses PCIe form factor exclusively. This enables multi-GPU scaling on either.
Which is cheaper to rent, the Quadro RTX 8000 or the V100?▾
Cloud rental prices for both the Quadro RTX 8000 and V100 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 Quadro RTX 8000 have compared to the V100?▾
The Quadro RTX 8000 has 48 GB of GDDR6 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find Quadro RTX 8000 and V100 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 Quadro RTX 8000 and the V100?▾
The Quadro RTX 8000 uses the Turing architecture (2018) while the V100 uses Volta (2017). The V100 delivers 7.7x the FP16 throughput and 1.3x the memory bandwidth of the Quadro RTX 8000.