Specifications Compared
| Spec | RTX-2070 | RTX-4080 |
|---|---|---|
| TDP | 175W | 320W |
| VRAM | 8 GB | 16 GB |
| CUDA Cores | 2,304 | 9,728 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Turing | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 288 | 304 |
| FP16 Performance | 7.5 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 7.5 TFLOPS | 48.7 TFLOPS |
| Memory Bandwidth | 448 GB/s | 717 GB/s |
Performance Analysis
The RTX 4080 demonstrates superior compute capability with 48.7 TFLOPS in FP16 and FP32 compared to the RTX 2070's 7.5 TFLOPS: this 6.5 times increase accelerates deep learning training and inference significantly. Training large neural networks benefits from the higher FP16 throughput, reducing epochs from days to hours on equivalent datasets. Inference tasks see similar gains, enabling higher requests per second in production deployments.
Memory specifications favor the RTX 4080 profoundly. Its 16 GB GDDR6X VRAM doubles the RTX 2070's 8 GB GDDR6, allowing larger models or batch sizes without out-of-memory errors: for instance, models exceeding 8 GB fit natively on the RTX 4080. The 717 GB/s bandwidth versus 448 GB/s supports 1.6 times faster data movement, minimizing bottlenecks during high-batch training and enabling larger effective batch sizes for stable gradients.
Power draw reflects these gains: the RTX 4080's 320 W TDP exceeds the RTX 2070's 175 W, but cloud providers optimize for density. Both use PCIe, though the RTX 2070's NVLink aids multi-GPU setups in specific cases.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4080 SUPER 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr | |||
RunPod | NVIDIA GeForce RTX 4080 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the RTX 2070
The RTX 2070 excels in cost-sensitive prototyping and small-scale machine learning tasks. With pricing from $0.02 per hour and an average of $0.04 per hour, it handles models fitting within 8 GB VRAM and 7.5 TFLOPS compute, such as basic inference or fine-tuning compact networks. Its 175 W TDP suits low-power cloud instances where budget trumps speed.
Legacy workflows or educational projects benefit from its availability across 2 live offers and NVLink support for linking multiple units affordably.
When to Choose the RTX 4080
The RTX 4080 is ideal for production-scale AI workloads requiring high performance. Its 48.7 TFLOPS FP16 and FP32 ratings, paired with 16 GB VRAM, manage large language models and complex training runs that exceed the RTX 2070's limits. The 717 GB/s bandwidth ensures efficient large-batch processing despite the $0.11 per hour starting price and $0.28 average.
Users prioritizing throughput over cost choose it for its 8 live offers and Ada Lovelace efficiencies in modern frameworks.
Use Cases
The RTX 4080's 16 GB VRAM and 48.7 TFLOPS FP16 performance support large models and batches, unlike the RTX 2070's 8 GB limit. Its 717 GB/s bandwidth prevents data stalls during extended training.
48.7 TFLOPS FP32 on the RTX 4080 delivers 6.5 times the throughput of the RTX 2070's 7.5 TFLOPS for high-query loads. 16 GB VRAM accommodates bigger models without quantization.
Small models fit the RTX 2070's 8 GB VRAM at low $0.02 per hour cost. Larger ones require the RTX 4080's 16 GB and higher compute.
The RTX 4080's 48.7 TFLOPS and 717 GB/s bandwidth generate images 6.5 times faster than the RTX 2070. 16 GB VRAM handles high-resolution workflows seamlessly.
FP32 performance of 48.7 TFLOPS on the RTX 4080 accelerates simulations over the RTX 2070's 7.5 TFLOPS. Higher bandwidth aids data-intensive HPC tasks.
Frequently Asked Questions
Which GPU has higher compute performance?▾
The RTX 4080 provides 48.7 TFLOPS in FP16 and FP32, compared to the RTX 2070's 7.5 TFLOPS. This results in a 6.5 times advantage for machine learning tasks. Cloud users see faster training times on the RTX 4080.
How do VRAM amounts compare?▾
RTX 4080 offers 16 GB GDDR6X, double the RTX 2070's 8 GB GDDR6. Larger VRAM enables bigger models on the RTX 4080. This matters for batch sizes in training.
What are the cloud pricing differences?▾
RTX 2070 starts at $0.02 per hour with $0.04 average across 2 offers. RTX 4080 begins at $0.11 per hour with $0.28 average across 8 offers. Budget tasks favor the RTX 2070.
Which is better for large model training?▾
RTX 4080 excels with 16 GB VRAM and 717 GB/s bandwidth versus RTX 2070's 8 GB and 448 GB/s. Its 48.7 TFLOPS handles demanding LLMs. RTX 2070 suits smaller models only.
Do they support the same form factors?▾
Both use PCIe form factor for cloud deployment. RTX 2070 adds NVLink interconnect for multi-GPU. RTX 4080 relies on standard PCIe scaling.
How does power consumption differ?▾
RTX 4080 TDP is 320 W, higher than RTX 2070's 175 W. This supports greater performance density. Cloud costs may reflect power usage indirectly.
Which is cheaper to rent, the RTX 2070 or the RTX 4080?▾
Cloud rental prices for both the RTX 2070 and RTX 4080 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 4080?▾
The RTX 2070 has 8 GB of GDDR6 memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find RTX 2070 and RTX 4080 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 4080?▾
The RTX 2070 uses the Turing architecture (2018) while the RTX 4080 uses Ada Lovelace (2022). The RTX 4080 delivers 6.5x the FP16 throughput and 1.6x the memory bandwidth of the RTX 2070.