Specifications Compared
| Spec | QUADRO-P4000 | RTX-4500-ADA |
|---|---|---|
| TDP | 105W | 210W |
| VRAM | 8 GB | 24 GB |
| CUDA Cores | 1,792 | 7,680 |
| Memory Type | GDDR5 | GDDR6 |
| Architecture | Pascal | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| FP16 Performance | 5.3 TFLOPS | 39.6 TFLOPS |
| FP32 Performance | 5.3 TFLOPS | 39.6 TFLOPS |
| Memory Bandwidth | 243 GB/s | 432 GB/s |
Performance Analysis
Compute performance shows a clear gap: the RTX 4500 Ada's 39.6 TFLOPS FP32 exceeds the Quadro P4000's 5.3 TFLOPS by a factor of 7.5. Both GPUs maintain equal FP16 and FP32 rates at 5.3 TFLOPS and 39.6 TFLOPS respectively, enabling efficient mixed-precision training and inference without precision bottlenecks. This delta translates to faster model training epochs and higher inference throughput on the 4500 Ada.
Memory capacity differs significantly: 24 GB GDDR6 on the 4500 Ada versus 8 GB GDDR5 on the P4000 allows larger batch sizes in deep learning, reducing out-of-memory errors for models exceeding 8 GB. Bandwidth at 432 GB/s on the 4500 Ada surpasses 243 GB/s on the P4000 by 78 percent, accelerating data transfers and supporting bigger batches without slowdowns.
Power consumption reflects capability: the 4500 Ada's 210W TDP doubles the P4000's 105W, demanding robust cooling but yielding higher output per instance in cloud environments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
Quadro P4000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro P4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Canada | $0.51/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro P4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.51/GPU/hr $1.02/hr total (2×) | Available | ||
Paperspace | 2×NVIDIA Quadro P4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | Canada | $0.51/GPU/hr $1.02/hr total (2×) | Available | ||
Paperspace | NVIDIA Quadro P4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Amsterdam | $0.51/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro P4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.51/GPU/hr | Available |
RTX 4500 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX 4500 Ada 24GB VRAM | 24GB | 0 vCPU 0GB RAM | 🌍global | $0.74/GPU/hr |
When to Choose the Quadro P4000
The Quadro P4000 fits scenarios with constrained power budgets: its 105W TDP consumes half the RTX 4500 Ada's 210W, ideal for edge deployments or shared cloud instances limiting total wattage. Legacy applications optimized for Pascal architecture run natively without recompilation, and six live cloud offers provide more availability than the 4500 Ada's three.
Workloads under 8 GB VRAM suffice here: tasks like basic CAD rendering or small-scale simulations leverage 243 GB/s bandwidth and 5.3 TFLOPS adequately at $0.51 per hour average cost.
When to Choose the RTX 4500 Ada
The RTX 4500 Ada excels in memory-intensive tasks: 24 GB GDDR6 handles large language models or high-resolution Stable Diffusion that exceed the P4000's 8 GB limit. Its 432 GB/s bandwidth supports bigger batches, cutting training time via 39.6 TFLOPS compute.
Modern Ada Lovelace features enhance ray tracing and tensor cores for AI: cloud users benefit from $0.34 per hour starting price matching average $0.51 per hour, despite 210W TDP.
Use Cases
The RTX 4500 Ada's 24 GB VRAM and 39.6 TFLOPS FP16 handle large models and batches that exceed the P4000's 8 GB and 5.3 TFLOPS limits.
39.6 TFLOPS FP32 on the 4500 Ada enables higher throughput for real-time serving versus the P4000's 5.3 TFLOPS.
432 GB/s bandwidth and 24 GB capacity on the 4500 Ada support efficient gradient updates on bigger datasets than the P4000's 243 GB/s and 8 GB.
Ada Lovelace architecture with 24 GB VRAM accelerates image generation at high resolutions, outperforming Pascal's 8 GB constraints.
P4000 suffices for small simulations at 105W TDP; 4500 Ada scales to complex ones with 39.6 TFLOPS and more VRAM.
Frequently Asked Questions
Which GPU has more VRAM?▾
The RTX 4500 Ada provides 24 GB GDDR6 VRAM. The Quadro P4000 offers 8 GB GDDR5. This tripling supports larger AI models.
What is the performance difference in TFLOPS?▾
RTX 4500 Ada delivers 39.6 TFLOPS FP32 and FP16. Quadro P4000 achieves 5.3 TFLOPS in both. The 4500 Ada is 7.5 times faster.
How do cloud prices compare?▾
Quadro P4000 starts at $0.51 per hour across six offers, averaging $0.51 per hour. RTX 4500 Ada starts at $0.34 per hour across three offers, averaging $0.51 per hour.
Which has higher memory bandwidth?▾
RTX 4500 Ada reaches 432 GB/s. Quadro P4000 provides 243 GB/s. The 78 percent increase aids data-heavy workloads.
What are the TDP ratings?▾
Quadro P4000 uses 105W TDP. RTX 4500 Ada requires 210W. Lower TDP suits power-limited setups.
Which architecture is newer?▾
RTX 4500 Ada uses Ada Lovelace from 2023. Quadro P4000 employs Pascal from 2017. Newer architecture includes advanced tensor cores.
Which is cheaper to rent, the Quadro P4000 or the RTX 4500 Ada?▾
Cloud rental prices for both the Quadro P4000 and RTX 4500 Ada 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 P4000 have compared to the RTX 4500 Ada?▾
The Quadro P4000 has 8 GB of GDDR5 memory. The RTX 4500 Ada has 24 GB of GDDR6 memory.
Can I find Quadro P4000 and RTX 4500 Ada 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 P4000 and the RTX 4500 Ada?▾
The Quadro P4000 uses the Pascal architecture (2017) while the RTX 4500 Ada uses Ada Lovelace (2023). The RTX 4500 Ada delivers 7.5x the FP16 throughput and 1.8x the memory bandwidth of the Quadro P4000.