Specifications Compared
| Spec | QUADRO-RTX-4000 | QUADRO-RTX-5000 |
|---|---|---|
| TDP | 160W | 230W |
| VRAM | 8 GB | 16 GB |
| CUDA Cores | 2,304 | 3,072 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Turing | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 288 | 384 |
| FP16 Performance | 7.1 TFLOPS | 11.2 TFLOPS |
| FP32 Performance | 7.1 TFLOPS | 11.2 TFLOPS |
| Memory Bandwidth | 416 GB/s | 448 GB/s |
Performance Analysis
Compute throughput defines a key advantage for the Quadro RTX 5000: its 11.2 TFLOPS in FP16 and FP32 exceeds the RTX 4000's 7.1 TFLOPS by 58 percent, accelerating neural network training epochs and inference queries in machine learning pipelines. FP16 performance matters for mixed-precision training, where the higher rate on the RTX 5000 reduces overall job times for models like transformers.
Memory capacity presents the starkest contrast: 16 GB GDDR6 on the RTX 5000 versus 8 GB on the RTX 4000 allows larger batch sizes during training, minimizing out-of-memory issues for datasets exceeding 8 GB. Bandwidth edges higher at 448 GB/s compared to 416 GB/s, easing data transfers in memory-intensive inference scenarios and enabling sustained performance without bottlenecks.
Power and interconnects influence deployment: the RTX 5000's 230W TDP demands more cooling than the 160W RTX 4000, but NVLink support facilitates scaled multi-GPU training, unlike the RTX 4000's standalone PCIe operation.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
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 |
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 4000
The Quadro RTX 4000 fits cost-sensitive projects requiring up to 8 GB VRAM: at an average $0.56 per hour, it delivers 7.1 TFLOPS FP16 and FP32 for visualization, light ML inference, or CAD rendering without excessive power draw. Its 160W TDP suits edge or power-constrained cloud instances, avoiding the RTX 5000's 230W demands.
When to Choose the Quadro RTX 5000
Opt for the Quadro RTX 5000 in memory-heavy workloads: 16 GB GDDR6 handles large models during training or fine-tuning, backed by 11.2 TFLOPS and 448 GB/s bandwidth. NVLink enables multi-GPU setups for distributed computing, justifying the $0.82 per hour average for high-throughput needs.
Use Cases
The RTX 5000's 16 GB VRAM and 11.2 TFLOPS handle larger language models and batch sizes better than the RTX 4000's 8 GB and 7.1 TFLOPS.
11.2 TFLOPS FP16 on the RTX 5000 lowers latency for inference on bigger models, with 448 GB/s bandwidth aiding throughput over the RTX 4000's specs.
Double VRAM at 16 GB on the RTX 5000 supports fine-tuning larger adapters without OOM errors, paired with 58 percent higher TFLOPS.
Both provide adequate 7.1 or 11.2 TFLOPS and Turing RT cores for generation; choose RTX 4000 for cost at $0.56 per hour if under 8 GB needs.
RTX 5000's NVLink and 16 GB VRAM enable multi-GPU simulations, with 11.2 TFLOPS outperforming RTX 4000 in FP32-bound HPC tasks.
Frequently Asked Questions
Which GPU has more VRAM, Quadro RTX 4000 or 5000?▾
The Quadro RTX 5000 has 16 GB GDDR6, double the RTX 4000's 8 GB. This allows the 5000 to manage larger datasets in training or rendering.
How do their compute performances compare?▾
The RTX 5000 achieves 11.2 TFLOPS in FP16 and FP32, 58 percent above the RTX 4000's 7.1 TFLOPS. This boosts ML training and inference speeds.
What are the current cloud prices?▾
RTX 4000 averages $0.56 per hour across five offers, while RTX 5000 averages $0.82 per hour across two. Prices reflect capability differences.
Do they support multi-GPU setups?▾
RTX 5000 includes NVLink for interconnects, unlike the PCIe-only RTX 4000. This aids scaled workloads on the 5000.
What are their power consumptions?▾
RTX 4000 draws 160W TDP, lower than RTX 5000's 230W. Lower TDP suits power-limited cloud instances for the 4000.
Are they the same architecture?▾
Both use Turing from 2018, sharing RT and Tensor cores. Differences stem from core counts yielding 7.1 versus 11.2 TFLOPS.
Which is cheaper to rent, the Quadro RTX 4000 or the Quadro RTX 5000?▾
Cloud rental prices for both the Quadro RTX 4000 and Quadro RTX 5000 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 4000 have compared to the Quadro RTX 5000?▾
The Quadro RTX 4000 has 8 GB of GDDR6 memory. The Quadro RTX 5000 has 16 GB of GDDR6 memory.
Can I find Quadro RTX 4000 and Quadro RTX 5000 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 4000 and the Quadro RTX 5000?▾
The Quadro RTX 4000 uses the Turing architecture (2018) while the Quadro RTX 5000 uses Turing (2018). The Quadro RTX 5000 delivers 1.6x the FP16 throughput and 1.1x the memory bandwidth of the Quadro RTX 4000.