Specifications Compared
| Spec | QUADRO-RTX-5000 | RTX-3080 |
|---|---|---|
| TDP | 230W | 320W |
| VRAM | 16 GB | 10-12 GB |
| CUDA Cores | 3,072 | 8,704 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Turing | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 384 | 272 |
| FP16 Performance | 11.2 TFLOPS | 29.8 TFLOPS |
| FP32 Performance | 11.2 TFLOPS | 29.8 TFLOPS |
| Memory Bandwidth | 448 GB/s | 760 GB/s |
Performance Analysis
The RTX 3080 demonstrates superior compute capability over the Quadro RTX 5000: 29.8 TFLOPS in FP16 and FP32 versus 11.2 TFLOPS, a 2.7-fold increase. This advantage translates to faster model training and inference in deep learning pipelines, where tensor core operations dominate; training epochs complete up to 2.7 times quicker on the RTX 3080 assuming compute-limited scenarios.
Memory bandwidth marks another key disparity: 760 GB/s on the RTX 3080 compared to 448 GB/s on the Quadro RTX 5000, enabling 70 percent higher data throughput. Larger batch sizes become viable in training, reducing per-iteration overhead and improving GPU utilization for tasks like LLM fine-tuning.
The Quadro RTX 5000 counters with 16 GB VRAM against the RTX 3080's 10 to 12 GB, accommodating bigger models or datasets without swapping. However, the RTX 3080's higher 320W TDP versus 230W demands more power infrastructure, potentially limiting dense deployments.
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
The Quadro RTX 5000 suits scenarios requiring 16 GB VRAM for large models or datasets that exceed the RTX 3080's 10 to 12 GB capacity. Its NVLink interconnect enables efficient multi-GPU scaling in professional simulations or rendering farms. At 230W TDP, it fits power-sensitive cloud instances better than the 320W RTX 3080.
When to Choose the RTX 3080
Opt for the RTX 3080 in compute-intensive workloads leveraging its 29.8 TFLOPS FP16 and FP32 performance, over 2.7 times the Quadro RTX 5000's 11.2 TFLOPS. The 760 GB/s bandwidth supports high-throughput inference and training with larger batches. Cloud pricing from $0.06 per hour averaging $0.13 delivers exceptional value across eight providers.
Use Cases
The RTX 3080's 29.8 TFLOPS FP16 performance and 760 GB/s bandwidth accelerate training cycles 2.7 times faster than the Quadro RTX 5000's 11.2 TFLOPS and 448 GB/s. Lower pricing at $0.06 per hour maximizes throughput per dollar.
Higher 29.8 TFLOPS FP32 on the RTX 3080 enables lower latency inference compared to 11.2 TFLOPS on the Quadro RTX 5000. Availability across eight providers at $0.13 average hourly rate supports scalable deployments.
RTX 3080 excels in compute-heavy fine-tuning with 29.8 TFLOPS, while Quadro RTX 5000's 16 GB VRAM handles larger models fitting poorly in 10 to 12 GB. Choice depends on model size and budget.
Ampere architecture and 760 GB/s bandwidth on RTX 3080 generate images faster than Turing's 448 GB/s on Quadro RTX 5000. Cost efficiency at $0.06 per hour suits iterative creative workflows.
Quadro RTX 5000's 16 GB VRAM and NVLink support memory-intensive simulations better than RTX 3080's 10 to 12 GB. Lower 230W TDP aids sustained precision computing.
Frequently Asked Questions
Which GPU has more VRAM, Quadro RTX 5000 or RTX 3080?▾
The Quadro RTX 5000 provides 16 GB GDDR6 VRAM, exceeding the RTX 3080's 10 to 12 GB GDDR6X. This makes the Quadro RTX 5000 preferable for memory-bound tasks. Both handle typical ML models, but larger datasets favor the Quadro.
What is the performance difference in TFLOPS?▾
RTX 3080 delivers 29.8 TFLOPS in FP16 and FP32, compared to 11.2 TFLOPS on Quadro RTX 5000. This yields up to 2.7 times faster compute for training and inference. Bandwidth also differs: 760 GB/s versus 448 GB/s.
Which is cheaper in the cloud?▾
RTX 3080 rentals start at $0.06 per hour, averaging $0.13 across eight offers. Quadro RTX 5000 averages $0.82 per hour over two offers. RTX 3080 provides better value for high-volume usage.
Does either support NVLink?▾
Quadro RTX 5000 includes NVLink for multi-GPU connectivity, absent on RTX 3080. This enables faster inter-GPU communication in scaled setups. Both use PCIe form factors.
What are the TDP ratings?▾
RTX 3080 has a 320W TDP, higher than Quadro RTX 5000's 230W. Higher TDP correlates with greater performance but requires robust power supplies. Cloud providers account for this in instance specs.
Which architecture is newer?▾
RTX 3080 uses Ampere from 2020, succeeding Quadro RTX 5000's Turing from 2018. Ampere offers improved tensor cores for 29.8 TFLOPS versus 11.2 TFLOPS. This generational edge boosts AI efficiency.
Which is cheaper to rent, the Quadro RTX 5000 or the RTX 3080?▾
Cloud rental prices for both the Quadro RTX 5000 and RTX 3080 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 3080?▾
The Quadro RTX 5000 has 16 GB of GDDR6 memory. The RTX 3080 has 10 to 12 GB of GDDR6X memory.
Can I find Quadro RTX 5000 and RTX 3080 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 3080?▾
The Quadro RTX 5000 uses the Turing architecture (2018) while the RTX 3080 uses Ampere (2020). The RTX 3080 delivers 2.7x the FP16 throughput and 1.7x the memory bandwidth of the Quadro RTX 5000.