Specifications Compared
| Spec | QUADRO-RTX-5000 | RTX-3070 |
|---|---|---|
| TDP | 230W | 220W |
| VRAM | 16 GB | 8 GB |
| CUDA Cores | 3,072 | 5,888 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Turing | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 384 | 184 |
| FP16 Performance | 11.2 TFLOPS | 20.3 TFLOPS |
| FP32 Performance | 11.2 TFLOPS | 20.3 TFLOPS |
| Memory Bandwidth | 448 GB/s | 448 GB/s |
Performance Analysis
The RTX 3070's Ampere architecture delivers 20.3 TFLOPS in both FP16 and FP32, surpassing the Quadro RTX 5000's 11.2 TFLOPS by 81 percent, which translates to faster model training and inference times in deep learning pipelines. This FP16 and FP32 parity on both GPUs supports mixed-precision training effectively, but the RTX 3070's higher throughput reduces epochs needed for convergence. Memory bandwidth matches at 448 GB/s, yet the Quadro's 16 GB VRAM versus 8 GB allows larger batch sizes in memory-intensive tasks like training large language models, preventing out-of-memory errors. The RTX 3070's lower TDP of 220W compared to 230W implies marginally better power efficiency per TFLOP. In real-world scenarios, the RTX 3070 excels in compute-bound workloads, while the Quadro handles data-bound applications with bigger datasets.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
Quadro RTX 5000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro RTX 5000 16GB VRAM | 16GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.82/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.82/GPU/hr $1.64/hr total (2×) | Available |
When to Choose the Quadro RTX 5000
Select the Quadro RTX 5000 for workloads demanding high VRAM capacity, such as training models exceeding 8 GB, where its 16 GB GDDR6 prevents batch size reductions. NVLink interconnect facilitates multi-GPU configurations for scaled professional simulations. Its enterprise-grade reliability suits CAD or scientific computing in cloud instances at $0.82 per hour.
When to Choose the RTX 3070
Opt for the RTX 3070 in cost-sensitive projects leveraging its 20.3 TFLOPS FP16 performance, nearly double the Quadro's 11.2 TFLOPS, for quicker inference and fine-tuning. With pricing from $0.04 per hour, it offers superior value across six providers for consumer-grade ML tasks fitting within 8 GB VRAM.
Use Cases
The Quadro RTX 5000's 16 GB VRAM supports larger batch sizes for LLMs compared to the RTX 3070's 8 GB. NVLink enables multi-GPU scaling for extended training runs.
RTX 3070's 20.3 TFLOPS FP16 outperforms the Quadro's 11.2 TFLOPS for faster token generation. Lower $0.04 per hour cost suits high-volume serving.
Both GPUs handle fine-tuning with matching 448 GB/s bandwidth, but RTX 3070's higher 20.3 TFLOPS speeds iterations while Quadro's 16 GB VRAM fits larger datasets.
RTX 3070's Ampere architecture and 20.3 TFLOPS deliver quicker image generation within 8 GB VRAM limits. Pricing at $0.04 per hour maximizes throughput.
Quadro RTX 5000's 16 GB VRAM and NVLink support complex simulations requiring high memory and multi-GPU coordination.
Frequently Asked Questions
Which GPU has more VRAM?▾
The Quadro RTX 5000 provides 16 GB GDDR6 VRAM, double the RTX 3070's 8 GB. This difference matters for workloads like large model training where memory constraints arise. Both share 448 GB/s bandwidth.
How do their compute performances compare?▾
RTX 3070 offers 20.3 TFLOPS in FP16 and FP32, 81 percent higher than Quadro RTX 5000's 11.2 TFLOPS. This boosts training and inference speeds significantly. Architectures differ: Ampere versus Turing.
What are the cloud rental prices?▾
RTX 3070 rents from $0.04 per hour average $0.08 across six offers, versus Quadro RTX 5000's $0.82 per hour across two. This makes RTX 3070 far more affordable for most users. Prices fluctuate with providers.
Does either support multi-GPU setups?▾
Quadro RTX 5000 includes NVLink for interconnect, enabling efficient multi-GPU operation. RTX 3070 lacks this, relying on PCIe alone. Choose Quadro for scaled professional tasks.
Which is more power efficient?▾
RTX 3070 has a 220W TDP versus Quadro RTX 5000's 230W, with 81 percent more performance per watt. This favors RTX 3070 in sustained cloud workloads. Both use PCIe form factor.
Is RTX 3070 newer than Quadro RTX 5000?▾
Yes, RTX 3070 uses 2020 Ampere architecture, while Quadro RTX 5000 is 2018 Turing. The newer design yields higher 20.3 TFLOPS versus 11.2 TFLOPS. This impacts software optimization.
Which is cheaper to rent, the Quadro RTX 5000 or the RTX 3070?▾
Cloud rental prices for both the Quadro RTX 5000 and RTX 3070 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 5000 have compared to the RTX 3070?▾
The Quadro RTX 5000 has 16 GB of GDDR6 memory. The RTX 3070 has 8 GB of GDDR6 memory.
Can I find Quadro RTX 5000 and RTX 3070 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 5000 and the RTX 3070?▾
The Quadro RTX 5000 uses the Turing architecture (2018) while the RTX 3070 uses Ampere (2020). The RTX 3070 delivers 1.8x the FP16 throughput and 1.0x the memory bandwidth of the Quadro RTX 5000.