Specifications Compared
| Spec | RTX-3070 | RTX-3090 |
|---|---|---|
| TDP | 220W | 350W |
| VRAM | 8 GB | 24 GB |
| CUDA Cores | 5,888 | 10,496 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ampere | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 184 | 328 |
| FP16 Performance | 20.3 TFLOPS | 35.6 TFLOPS |
| FP32 Performance | 20.3 TFLOPS | 35.6 TFLOPS |
| Memory Bandwidth | 448 GB/s | 936 GB/s |
Performance Analysis
Compute performance favors the RTX 3090 decisively: its 35.6 TFLOPS in FP16 and FP32 exceeds the RTX 3070's 20.3 TFLOPS by 75 percent. This delta translates to faster model training and inference times, especially in mixed-precision workflows common in deep learning. Training large neural networks benefits from the higher throughput, reducing epochs from hours to minutes on equivalent datasets.
Memory capacity is the standout differentiator: 24 GB GDDR6X on the RTX 3090 supports models exceeding 8 GB GDDR6 limits of the RTX 3070, enabling full fine-tuning of large language models without quantization. Bandwidth at 936 GB/s versus 448 GB/s allows larger batch sizes, minimizing data loading bottlenecks and improving GPU utilization during inference.
Power and interconnects influence scalability. The RTX 3070's 220W TDP suits low-cost, single-GPU setups, while the RTX 3090's 350W and NVLink enable multi-GPU configurations for distributed training.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 3090
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 0 vCPU 0GB RAM | Wilmington, Delaware | $0.20/GPU/hr | Available | ||
TensorDock | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 0 vCPU 0GB RAM | Dallas, Texas | $0.21/GPU/hr | Available | ||
 Vast.ai | 4×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 32 vCPU 403GB RAM 104GB Storage | Iceland | $0.25/GPU/hr $1.01/hr total (4×) | Available | ||
Vast.ai | 4×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 32 vCPU 252GB RAM 1440GB Storage | Finland | $0.27/GPU/hr $1.07/hr total (4×) | Available | ||
 LeaderGPU | 8×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.29/GPU/hr $2.29/hr total (8×) | Available |
When to Choose the RTX 3070
The RTX 3070 excels in budget-constrained scenarios fitting within 8 GB VRAM. Prototyping small models or inference on datasets under 448 GB/s bandwidth demands favors its $0.04 per hour starting price and 20.3 TFLOPS performance. Low 220W TDP reduces cloud hosting costs for lightweight tasks like basic fine-tuning.
When to Choose the RTX 3090
Opt for the RTX 3090 when workloads demand 24 GB VRAM or exceed 8 GB limits. High-bandwidth tasks at 936 GB/s and 35.6 TFLOPS accelerate large-scale training and inference. NVLink support and availability across 50 offers at $0.08 per hour starting price justify it for production environments.
Use Cases
The RTX 3090's 24 GB VRAM accommodates full model training without splitting, unlike the RTX 3070's 8 GB limit. Its 35.6 TFLOPS and 936 GB/s bandwidth speed up convergence on large datasets.
24 GB VRAM on the RTX 3090 supports longer contexts and higher concurrency than 8 GB on the RTX 3070. 936 GB/s bandwidth sustains large batch inference without bottlenecks.
RTX 3090's 35.6 TFLOPS and 24 GB VRAM enable efficient fine-tuning of billion-parameter models. RTX 3070's 8 GB restricts it to smaller adapters or heavy quantization.
Both GPUs handle image generation well within 8 GB VRAM via optimizations, but RTX 3090's 24 GB allows higher resolutions. RTX 3070 suffices at lower $0.08 per hour average cost.
RTX 3070's 220W TDP and $0.04 per hour pricing fit simulations under 20.3 TFLOPS FP32. Larger 936 GB/s on RTX 3090 is overkill for many serial computations.
Frequently Asked Questions
Which has more VRAM: RTX 3070 or RTX 3090?▾
The RTX 3090 provides 24 GB GDDR6X VRAM, compared to 8 GB GDDR6 on the RTX 3070. This makes the RTX 3090 suitable for larger models. Memory bandwidth follows at 936 GB/s versus 448 GB/s.
RTX 3070 vs RTX 3090 for machine learning?▾
RTX 3090 offers 35.6 TFLOPS FP16/FP32 versus RTX 3070's 20.3 TFLOPS, ideal for training. RTX 3070 works for inference on small models at lower cost. Both use Ampere architecture from 2020.
What is the price difference in cloud rentals?▾
RTX 3070 starts at $0.04 per hour with $0.08 average across 6 offers. RTX 3090 begins at $0.08 per hour averaging $0.42 across 50 offers. Budget tasks favor RTX 3070.
Does RTX 3090 support NVLink?▾
Yes, RTX 3090 includes NVLink for multi-GPU scaling. RTX 3070 lacks this interconnect. Both use PCIe form factor.
Power consumption comparison?▾
RTX 3070 has 220W TDP, lower than RTX 3090's 350W. This impacts cloud costs for long runs. Higher TDP on RTX 3090 enables greater performance.
Are they the same generation?▾
Both RTX 3070 and RTX 3090 use Ampere architecture from 2020. Differences lie in VRAM, bandwidth, and compute. They compete directly in cloud ML rentals.
Which is cheaper to rent, the RTX 3070 or the RTX 3090?▾
Cloud rental prices for both the RTX 3070 and RTX 3090 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 3070 have compared to the RTX 3090?▾
The RTX 3070 has 8 GB of GDDR6 memory. The RTX 3090 has 24 GB of GDDR6X memory.
Can I find RTX 3070 and RTX 3090 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 3070 and the RTX 3090?▾
The RTX 3070 uses the Ampere architecture (2020) while the RTX 3090 uses Ampere (2020). The RTX 3090 delivers 1.8x the FP16 throughput and 2.1x the memory bandwidth of the RTX 3070.