Specifications Compared
| Spec | QUADRO-RTX-5000 | RTX-4070 |
|---|---|---|
| TDP | 230W | 200W |
| VRAM | 16 GB | 12 GB |
| CUDA Cores | 3,072 | 5,888 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Turing | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 384 | 184 |
| FP16 Performance | 11.2 TFLOPS | 29.1 TFLOPS |
| FP32 Performance | 11.2 TFLOPS | 29.1 TFLOPS |
| Memory Bandwidth | 448 GB/s | 504 GB/s |
Performance Analysis
The RTX 4070's 29.1 TFLOPS in FP16 and FP32 doubles the Quadro RTX 5000's 11.2 TFLOPS, accelerating machine learning training cycles and inference throughput significantly. In training, higher FP16 performance reduces epochs needed for convergence; for inference, FP32 parity ensures precise real-time predictions at faster speeds.
Memory bandwidth of 504 GB/s on the RTX 4070 enables larger batch sizes than the Quadro's 448 GB/s, minimizing data transfer bottlenecks in deep learning pipelines and improving GPU utilization. The Ada Lovelace design pairs this with a 200W TDP, lower than the Quadro's 230W, for better power efficiency in prolonged cloud sessions.
Despite less VRAM at 12 GB versus 16 GB, the RTX 4070's architectural advancements mitigate this in most scenarios, though Quadro excels in VRAM-saturated tasks like large matrix multiplications. NVLink on Quadro supports multi-GPU scaling absent on RTX 4070, aiding distributed computing.
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 |
RTX 4070
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the Quadro RTX 5000
The Quadro RTX 5000 excels in professional workflows requiring NVLink for multi-GPU interconnects and 16 GB GDDR6 VRAM for memory-heavy applications such as CAD simulations or certified workstation software. Its Turing architecture ensures compatibility with legacy enterprise tools where RTX 4070 lacks certification, justifying $0.82 per hour despite fewer offers.
When to Choose the RTX 4070
The RTX 4070 dominates cost-effective modern AI and graphics tasks with 29.1 TFLOPS FP16/FP32 performance and 504 GB/s bandwidth at an average $0.19 per hour across 9 offers. Lower 200W TDP suits dense cloud deployments, while Ada Lovelace optimizations boost efficiency in training, inference, and generative AI over the older Quadro RTX 5000.
Use Cases
RTX 4070's 29.1 TFLOPS FP16 doubles Quadro RTX 5000's 11.2 TFLOPS for faster convergence. Average $0.19 per hour pricing enhances scalability across sessions.
Higher 504 GB/s bandwidth supports larger batches than 448 GB/s, reducing latency. Ada architecture yields efficient real-time serving at $0.07 per hour starting price.
29.1 TFLOPS FP32 outperforms 11.2 TFLOPS, shortening iteration times. Cost advantage at average $0.19 per hour suits iterative development.
Ada Lovelace optimizations and 29.1 TFLOPS accelerate image generation over Turing's 11.2 TFLOPS. Low $0.07 per hour entry enables high-volume creative workflows.
16 GB VRAM handles larger datasets than 12 GB; NVLink enables multi-GPU scaling for simulations absent on RTX 4070.
Frequently Asked Questions
Which GPU performs better in FP32 compute?▾
The RTX 4070 achieves 29.1 TFLOPS FP32, surpassing the Quadro RTX 5000's 11.2 TFLOPS. This doubles training and simulation speeds. Bandwidth at 504 GB/s further aids data-intensive calculations.
Does Quadro RTX 5000 have more VRAM?▾
Yes, Quadro RTX 5000 offers 16 GB GDDR6 versus RTX 4070's 12 GB GDDR6X. It suits memory-bound tasks like large models. RTX 4070 compensates with 504 GB/s bandwidth over 448 GB/s.
What is the price difference in cloud rentals?▾
RTX 4070 starts at $0.07 per hour averaging $0.19 across 9 offers; Quadro RTX 5000 is $0.82 per hour average across 2 offers. This yields 4x to 10x savings for RTX 4070. Performance at 29.1 TFLOPS justifies the value.
Which has lower power consumption?▾
RTX 4070's 200W TDP is lower than Quadro RTX 5000's 230W. It enables denser cloud packing. Efficiency pairs with 29.1 TFLOPS for sustained workloads.
Is NVLink available on RTX 4070?▾
No, RTX 4070 lacks NVLink interconnect present on Quadro RTX 5000. Quadro supports multi-GPU professional scaling. RTX 4070 relies on PCIe for 504 GB/s bandwidth tasks.
Which architecture is newer?▾
RTX 4070 uses Ada Lovelace from 2023, versus Quadro RTX 5000's Turing from 2018. Ada delivers 29.1 TFLOPS and optimizations. This drives AI advantages over legacy design.
Which is cheaper to rent, the Quadro RTX 5000 or the RTX 4070?▾
Cloud rental prices for both the Quadro RTX 5000 and RTX 4070 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 4070?▾
The Quadro RTX 5000 has 16 GB of GDDR6 memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find Quadro RTX 5000 and RTX 4070 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 4070?▾
The Quadro RTX 5000 uses the Turing architecture (2018) while the RTX 4070 uses Ada Lovelace (2023). The RTX 4070 delivers 2.6x the FP16 throughput and 1.1x the memory bandwidth of the Quadro RTX 5000.