Specifications Compared
| Spec | QUADRO-RTX-8000 | RTX-4000-ADA |
|---|---|---|
| TDP | 260W | 130W |
| VRAM | 48 GB | 20 GB |
| CUDA Cores | 4,608 | 6,144 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Turing | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 576 | 192 |
| FP16 Performance | 16.3 TFLOPS | 26.7 TFLOPS |
| FP32 Performance | 16.3 TFLOPS | 26.7 TFLOPS |
| Memory Bandwidth | 672 GB/s | 360 GB/s |
Performance Analysis
The RTX 4000 Ada's FP16 and FP32 performance reaches 26.7 TFLOPS, a 64 percent increase over the Quadro RTX 8000's 16.3 TFLOPS, accelerating deep learning training and inference by handling more operations per second. This uplift from Ada Lovelace architecture benefits tensor core-intensive workloads, reducing epoch times in model optimization.
Memory bandwidth presents a key divergence: the Quadro RTX 8000's 672 GB/s enables larger batch sizes in data-heavy training compared to the RTX 4000 Ada's 360 GB/s, minimizing data starvation in VRAM-constrained scenarios. However, the Ada's halved TDP at 130W versus 260W supports denser cloud deployments with lower cooling demands.
In practice, inference pipelines favor the RTX 4000 Ada's higher throughput for real-time applications, while the Quadro RTX 8000 suits memory-bound simulations requiring sustained high-bandwidth access.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4000 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.26/GPU/hr | |||
 Vast.ai | 2×NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 64 vCPU 84GB RAM 1010GB Storage | Hungary | $0.40/GPU/hr $0.80/hr total (2×) | Available | ||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.44/GPU/hr | |||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 0 vCPU 0GB RAM | 🌍global | $0.57/GPU/hr |
When to Choose the Quadro RTX 8000
The Quadro RTX 8000 stands out for workloads needing substantial VRAM, such as training massive models exceeding 20 GB or large-scale scientific simulations leveraging 48 GB GDDR6. Its 672 GB/s bandwidth and NVLink interconnect facilitate multi-GPU setups for datasets that overwhelm single-card limits on newer GPUs.
When to Choose the RTX 4000 Ada
The RTX 4000 Ada proves ideal for efficiency-focused tasks like inference serving or fine-tuning, where 26.7 TFLOPS outperforms the Quadro's 16.3 TFLOPS and 130W TDP cuts operational costs. Cloud users benefit from pricing starting at $0.09 per hour across nine providers.
Use Cases
The Quadro RTX 8000's 48 GB VRAM handles large batch sizes for training massive LLMs that exceed the RTX 4000 Ada's 20 GB limit. Its 672 GB/s bandwidth sustains data flow in memory-intensive phases.
The RTX 4000 Ada's 26.7 TFLOPS in FP16 delivers 64 percent faster inference than the Quadro RTX 8000's 16.3 TFLOPS. Lower 130W TDP enables scalable serving.
RTX 4000 Ada's higher 26.7 TFLOPS accelerates fine-tuning iterations over the Quadro's 16.3 TFLOPS. Cost-effective cloud pricing from $0.09 per hour suits iterative workflows.
Ada Lovelace architecture in RTX 4000 Ada optimizes generative tasks with 26.7 TFLOPS, outperforming Turing-based Quadro RTX 8000. Efficient 130W power draw supports prolonged generation runs.
Quadro RTX 8000's 48 GB VRAM and 672 GB/s bandwidth manage large datasets in simulations better than RTX 4000 Ada's 20 GB and 360 GB/s. NVLink aids multi-GPU scaling.
Frequently Asked Questions
Which GPU has more VRAM?▾
The Quadro RTX 8000 provides 48 GB GDDR6 VRAM, double the RTX 4000 Ada's 20 GB. This makes the Quadro suitable for memory-intensive tasks like large model training.
What is the performance difference in TFLOPS?▾
The RTX 4000 Ada achieves 26.7 TFLOPS in both FP16 and FP32, surpassing the Quadro RTX 8000's 16.3 TFLOPS by 64 percent. This boosts training and inference speeds.
How do power consumptions compare?▾
RTX 4000 Ada draws 130W TDP, half the Quadro RTX 8000's 260W. Lower power enables more efficient cloud and multi-GPU deployments.
What are the cloud prices for RTX 4000 Ada?▾
RTX 4000 Ada starts at $0.09 per hour, averaging $0.22 per hour across nine live offers. Quadro RTX 8000 has no current live cloud offers.
Which architecture is newer?▾
RTX 4000 Ada uses Ada Lovelace from 2023, while Quadro RTX 8000 relies on Turing from 2018. Ada provides architectural gains in compute efficiency.
Does Quadro RTX 8000 support NVLink?▾
Yes, Quadro RTX 8000 includes NVLink for multi-GPU connectivity, unlike RTX 4000 Ada. This aids scaling for high-memory workloads.
Which is cheaper to rent, the Quadro RTX 8000 or the RTX 4000 Ada?▾
Cloud rental prices for both the Quadro RTX 8000 and RTX 4000 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 RTX 8000 have compared to the RTX 4000 Ada?▾
The Quadro RTX 8000 has 48 GB of GDDR6 memory. The RTX 4000 Ada has 20 GB of GDDR6 memory.
Can I find Quadro RTX 8000 and RTX 4000 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 RTX 8000 and the RTX 4000 Ada?▾
The Quadro RTX 8000 uses the Turing architecture (2018) while the RTX 4000 Ada uses Ada Lovelace (2023). The RTX 4000 Ada delivers 1.6x the FP16 throughput and 1.9x the memory bandwidth of the Quadro RTX 8000.