Specifications Compared
| Spec | QUADRO-RTX-8000 | RTX-3070 |
|---|---|---|
| TDP | 260W | 220W |
| VRAM | 48 GB | 8 GB |
| CUDA Cores | 4,608 | 5,888 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Turing | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 576 | 184 |
| FP16 Performance | 16.3 TFLOPS | 20.3 TFLOPS |
| FP32 Performance | 16.3 TFLOPS | 20.3 TFLOPS |
| Memory Bandwidth | 672 GB/s | 448 GB/s |
Performance Analysis
The RTX 3070 demonstrates superior raw compute with 20.3 TFLOPS in both FP16 and FP32 compared to the Quadro RTX 8000's 16.3 TFLOPS: this edge accelerates deep learning training cycles and inference passes by approximately 24 percent in compute-bound scenarios. Equal FP16 to FP32 ratios on both GPUs indicate balanced half-precision and single-precision performance suited for mixed-precision training in modern frameworks.
The Quadro RTX 8000's 48 GB VRAM dwarfs the RTX 3070's 8 GB, enabling larger batch sizes in model training: for instance, it accommodates datasets that exceed 8 GB without gradient checkpointing or model sharding. Higher memory bandwidth at 672 GB/s versus 448 GB/s further reduces latency in data transfers, benefiting memory-intensive inference on oversized models.
Ampere's architectural advancements in the RTX 3070 yield better tensor core utilization despite lower bandwidth, while the Quadro RTX 8000's 260W TDP exceeds the 220W of its counterpart, impacting power efficiency in prolonged cloud runs.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
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When to Choose the Quadro RTX 8000
The Quadro RTX 8000 stands out for memory-dominated workloads: its 48 GB GDDR6 VRAM handles large-scale simulations and rendering scenes that surpass the RTX 3070's 8 GB limit. NVLink interconnect supports multi-GPU scaling for distributed training on datasets exceeding single-GPU capacity.
Professionals in CAD or scientific visualization select it when 672 GB/s bandwidth ensures smooth handling of high-resolution textures without bottlenecks.
When to Choose the RTX 3070
The RTX 3070 proves ideal for cost-sensitive deployments: cloud pricing from $0.04 per hour averaging $0.08 per hour across six offers makes it accessible for prototyping. Its 20.3 TFLOPS FP16 and FP32 performance delivers faster iterations than the Quadro RTX 8000's 16.3 TFLOPS.
Lower 220W TDP suits high-density cloud racks, and Ampere architecture optimizes lighter AI tasks without needing 48 GB VRAM.
Use Cases
The Quadro RTX 8000's 48 GB VRAM supports larger models and batch sizes critical for LLM training, unlike the RTX 3070's 8 GB limit. Its 672 GB/s bandwidth minimizes data loading delays during extended sessions.
RTX 3070's 20.3 TFLOPS FP16 performance handles inference on models fitting within 8 GB VRAM more efficiently than the Quadro RTX 8000's 16.3 TFLOPS. Low $0.08 per hour pricing enables high-throughput serving.
Smaller fine-tuning datasets fit RTX 3070's 8 GB VRAM with 20.3 TFLOPS speed, but Quadro RTX 8000's 48 GB excels for parameter-heavy models. Choice depends on model size and budget.
RTX 3070's 8 GB VRAM suffices for most Stable Diffusion pipelines at 20.3 TFLOPS, outperforming Quadro RTX 8000's 16.3 TFLOPS. Affordable cloud access at $0.04 per hour accelerates image generation.
Quadro RTX 8000's 48 GB VRAM and NVLink manage large simulations better than RTX 3070's 8 GB. 672 GB/s bandwidth supports complex dataset processing.
Frequently Asked Questions
Which GPU has more VRAM, Quadro RTX 8000 or RTX 3070?▾
The Quadro RTX 8000 provides 48 GB GDDR6 VRAM, far exceeding the RTX 3070's 8 GB GDDR6. This makes the Quadro suitable for memory-intensive tasks. The RTX 3070 compensates with higher 20.3 TFLOPS performance.
How do their compute performances compare?▾
RTX 3070 delivers 20.3 TFLOPS in FP16 and FP32, surpassing Quadro RTX 8000's 16.3 TFLOPS in both. This benefits training and inference speed. Architecture differences favor Ampere for efficiency.
What is the memory bandwidth difference?▾
Quadro RTX 8000 offers 672 GB/s bandwidth versus RTX 3070's 448 GB/s. Higher bandwidth aids data-heavy workloads. It pairs with 48 GB VRAM for large batches.
Is RTX 3070 available in the cloud?▾
RTX 3070 has live cloud offers from $0.04 per hour, averaging $0.08 per hour across six providers. Quadro RTX 8000 shows no live offers. This availability drives its popularity.
Which has lower power consumption?▾
RTX 3070's 220W TDP is lower than Quadro RTX 8000's 260W. This improves efficiency in cloud deployments. It supports denser instance configurations.
Does Quadro RTX 8000 support multi-GPU?▾
Quadro RTX 8000 includes NVLink for multi-GPU interconnects, absent in RTX 3070. This enables scaled scientific computing. PCIe form factor is common to both.
Which is cheaper to rent, the Quadro RTX 8000 or the RTX 3070?▾
Cloud rental prices for both the Quadro RTX 8000 and RTX 3070 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 3070?▾
The Quadro RTX 8000 has 48 GB of GDDR6 memory. The RTX 3070 has 8 GB of GDDR6 memory.
Can I find Quadro RTX 8000 and RTX 3070 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 3070?▾
The Quadro RTX 8000 uses the Turing architecture (2018) while the RTX 3070 uses Ampere (2020). The RTX 3070 delivers 1.2x the FP16 throughput and 1.5x the memory bandwidth of the Quadro RTX 8000.