Specifications Compared
| Spec | RTX-2070 | RTX-5000-ADA |
|---|---|---|
| TDP | 175W | 250W |
| VRAM | 8 GB | 32 GB |
| CUDA Cores | 2,304 | 12,800 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Turing | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 288 | 400 |
| FP16 Performance | 7.5 TFLOPS | 65.3 TFLOPS |
| FP32 Performance | 7.5 TFLOPS | 65.3 TFLOPS |
| Memory Bandwidth | 448 GB/s | 576 GB/s |
Performance Analysis
Compute performance defines the primary distinction: the RTX 5000 Ada's 65.3 TFLOPS in FP16 and FP32 dwarfs the RTX 2070 SUPER's 9.1 TFLOPS, enabling up to seven times faster model training and inference for deep learning tasks. This delta translates to shorter epochs in training large neural networks and higher throughput in inference servers handling concurrent requests.
Memory specifications further favor the RTX 5000 Ada. Its 32 GB VRAM supports batch sizes and model complexities infeasible on the RTX 2070 SUPER's 8 GB limit, such as fine-tuning billion-parameter LLMs without gradient checkpointing. The 576 GB/s bandwidth versus 448 GB/s sustains higher data transfer rates, reducing bottlenecks in memory-intensive operations like Stable Diffusion generation or scientific simulations.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 5000 Ada Generation
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Chubbuck, Idaho | $0.55/GPU/hr | Available | ||
 RunPod | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 10 vCPU 83GB RAM | 🌍global | $0.83/GPU/hr |
When to Choose the RTX 2070 SUPER
The RTX 2070 SUPER fits scenarios with strict power or cost constraints. Its 215 W TDP consumes less energy than the RTX 5000 Ada's 250 W, ideal for local desktops or edge devices running lightweight inference on models under 8 GB VRAM. No current cloud offers exist, so it suits users with existing hardware for prototyping small-scale AI tasks.
When to Choose the RTX 5000 Ada Generation
Opt for the RTX 5000 Ada in production environments requiring high performance and capacity. The 32 GB VRAM and 65.3 TFLOPS handle large-scale LLM training or inference, with cloud availability from $0.25 per hour enabling scalable deployments without upfront hardware costs.
Use Cases
The RTX 5000 Ada's 32 GB VRAM and 65.3 TFLOPS FP16 performance support training large language models with bigger batches, unlike the RTX 2070 SUPER's 8 GB limit and 9.1 TFLOPS.
High FP16 throughput of 65.3 TFLOPS on the RTX 5000 Ada enables low-latency serving of massive LLMs, far exceeding the RTX 2070 SUPER's capabilities for production-scale deployments.
Fine-tuning mid-sized models benefits from the RTX 5000 Ada's 32 GB VRAM for full precision and 576 GB/s bandwidth, avoiding the RTX 2070 SUPER's memory constraints.
Stable Diffusion workflows fit within 8 GB VRAM on the RTX 2070 SUPER for basic generation, but the RTX 5000 Ada's higher performance accelerates iterations with larger batches.
Compute-intensive simulations leverage the RTX 5000 Ada's 65.3 TFLOPS FP32 and 576 GB/s bandwidth for faster results compared to the RTX 2070 SUPER's 9.1 TFLOPS.
Frequently Asked Questions
What is the FP32 performance difference between RTX 2070 SUPER and RTX 5000 Ada?▾
The RTX 5000 Ada delivers 65.3 TFLOPS FP32, over seven times the RTX 2070 SUPER's 9.1 TFLOPS. This gap accelerates AI training and compute workloads significantly.
How much VRAM do these GPUs have?▾
The RTX 2070 SUPER offers 8 GB GDDR6, sufficient for small models. The RTX 5000 Ada provides 32 GB GDDR6, enabling larger models and batch sizes.
What are the power requirements?▾
RTX 2070 SUPER has a 215 W TDP, lower than the RTX 5000 Ada's 250 W. This makes the SUPER more efficient for power-sensitive setups.
Is RTX 5000 Ada available on cloud?▾
Yes, RTX 5000 Ada cloud pricing starts at $0.25 per hour, averaging $0.51 per hour across five providers. RTX 2070 SUPER has no live cloud offers.
Which has higher memory bandwidth?▾
RTX 5000 Ada achieves 576 GB/s, 29 percent more than RTX 2070 SUPER's 448 GB/s. Higher bandwidth reduces data transfer bottlenecks in ML tasks.
What architectures do they use?▾
RTX 2070 SUPER uses Turing from 2019, while RTX 5000 Ada employs Ada Lovelace from 2023. The newer architecture yields superior efficiency and performance.
Which is cheaper to rent, the RTX 2070 or the RTX 5000 Ada?▾
Cloud rental prices for both the RTX 2070 and RTX 5000 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 RTX 2070 have compared to the RTX 5000 Ada?▾
The RTX 2070 has 8 GB of GDDR6 memory. The RTX 5000 Ada has 32 GB of GDDR6 memory.
Can I find RTX 2070 and RTX 5000 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 RTX 2070 and the RTX 5000 Ada?▾
The RTX 2070 uses the Turing architecture (2018) while the RTX 5000 Ada uses Ada Lovelace (2023). The RTX 5000 Ada delivers 8.7x the FP16 throughput and 1.3x the memory bandwidth of the RTX 2070.