Specifications Compared
| Spec | RTX-2070 | RTX-5090 |
|---|---|---|
| TDP | 175W | 575W |
| VRAM | 8 GB | 32 GB |
| CUDA Cores | 2,304 | 21,760 |
| Memory Type | GDDR6 | GDDR7 |
| Architecture | Turing | Blackwell |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | PCIe 5.0 |
| Tensor Cores | 288 | 680 |
| FP16 Performance | 7.5 TFLOPS | 419 TFLOPS |
| FP32 Performance | 7.5 TFLOPS | 105 TFLOPS |
| Memory Bandwidth | 448 GB/s | 1,792 GB/s |
Performance Analysis
Spec differences translate to vast real-world performance gaps in machine learning. The RTX 5090's 419 TFLOPS FP16 vastly exceeds the RTX 2070 SUPER's 9 TFLOPS, accelerating training and inference in half-precision formats common in frameworks like TensorFlow. Its FP32 at 105 TFLOPS versus 9 TFLOPS supports precise scientific simulations, while FP8 at 838 TFLOPS optimizes quantized inference for large language models.
Memory bandwidth of 1792 GB/s on the RTX 5090 enables larger batch sizes during training, minimizing data loading bottlenecks and improving throughput for datasets over 8 GB, which overwhelm the RTX 2070 SUPER's 448 GB/s and 8 GB VRAM. The higher 575 W TDP allows sustained peak performance under heavy loads, unlike the 215 W limit that throttles the older card in prolonged sessions. These factors make the RTX 5090 ideal for scalable AI pipelines.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 5090
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA GeForce RTX 5090 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Chubbuck, Idaho | $0.57/GPU/hr | Available | ||
 Vast.ai | NVIDIA GeForce RTX 5090 32GB VRAM | 32GB | 8 vCPU 30GB RAM 489GB Storage | South Korea | $0.87/GPU/hr | Available | ||
Vast.ai | NVIDIA GeForce RTX 5090 32GB VRAM | 32GB | 16 vCPU 30GB RAM 583GB Storage | South Korea | $0.87/GPU/hr | Available | ||
Vast.ai | NVIDIA GeForce RTX 5090 32GB VRAM | 32GB | 384 vCPU 94GB RAM 642GB Storage | Czechia | $0.89/GPU/hr | Available | ||
Vast.ai | NVIDIA GeForce RTX 5090 32GB VRAM | 32GB | 16 vCPU 30GB RAM 495GB Storage | South Korea | $0.91/GPU/hr | Available |
When to Choose the RTX 2070 SUPER
The RTX 2070 SUPER excels in cost-sensitive, local setups with modest power envelopes. Its 215 W TDP integrates easily into consumer PCs without PSU upgrades, and 8 GB VRAM handles lightweight fine-tuning or inference on models under 3 billion parameters. Users avoiding cloud dependency favor it for owned hardware lacking live rental offers.
When to Choose the RTX 5090
Opt for the RTX 5090 in high-throughput AI and rendering tasks demanding extensive resources. 32 GB VRAM accommodates full training of large models, and 1792 GB/s bandwidth supports massive batches. Cloud pricing from $0.09 per hour offers flexible scaling for professionals.
Use Cases
RTX 5090's 32 GB VRAM and 1792 GB/s bandwidth handle large datasets and batches for billion-parameter LLMs; RTX 2070 SUPER's 8 GB VRAM causes out-of-memory errors.
838 TFLOPS FP8 and 419 TFLOPS FP16 enable low-latency serving of large models; 2070 SUPER lacks VRAM and speed for production-scale inference.
105 TFLOPS FP32 accelerates parameter-efficient methods like LoRA on mid-sized models; 2070 SUPER suffices for tiny models but bottlenecks larger ones.
RTX 2070 SUPER's 8 GB VRAM runs 512x512 generations adequately; RTX 5090 excels at high-res 4K with faster iteration via 419 TFLOPS FP16.
RTX 5090's 105 TFLOPS FP32 and 32 GB VRAM support complex simulations; 2070 SUPER's 9 TFLOPS limits to small-scale problems.
Frequently Asked Questions
What is the VRAM difference between RTX 2070 SUPER and RTX 5090?▾
The RTX 2070 SUPER has 8 GB GDDR6 VRAM, while the RTX 5090 offers 32 GB GDDR7. This quadruples capacity for larger models on the 5090.
How do FP32 performance specs compare?▾
RTX 2070 SUPER delivers 9 TFLOPS FP32, versus RTX 5090's 105 TFLOPS. The 5090 provides over 11x higher single-precision compute for simulations.
What are the cloud prices for RTX 5090?▾
Current pricing starts at $0.09 per hour, averaging $0.62 per hour across 30 live offers. No live offers exist for RTX 2070 SUPER.
Is RTX 2070 SUPER suitable for LLM inference?▾
Its 8 GB VRAM and 9 TFLOPS FP16 limit it to small models under 7B parameters. RTX 5090's 419 TFLOPS FP16 handles production-scale LLMs efficiently.
What TDP do these GPUs have?▾
RTX 2070 SUPER requires 215 W TDP, fitting standard PSUs. RTX 5090 demands 575 W, necessitating robust cooling and power for sustained loads.
Which has higher memory bandwidth?▾
RTX 5090 achieves 1792 GB/s, four times the RTX 2070 SUPER's 448 GB/s. This boosts batch processing on the newer GPU.
Which is cheaper to rent, the RTX 2070 or the RTX 5090?▾
Cloud rental prices for both the RTX 2070 and RTX 5090 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 5090?▾
The RTX 2070 has 8 GB of GDDR6 memory. The RTX 5090 has 32 GB of GDDR7 memory.
Can I find RTX 2070 and RTX 5090 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 5090?▾
The RTX 2070 uses the Turing architecture (2018) while the RTX 5090 uses Blackwell (2025). The RTX 5090 delivers 55.9x the FP16 throughput and 4.0x the memory bandwidth of the RTX 2070.