Specifications Compared
| Spec | RTX-3070 | RTX-4080 |
|---|---|---|
| TDP | 220W | 320W |
| VRAM | 8 GB | 16 GB |
| CUDA Cores | 5,888 | 9,728 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 184 | 304 |
| FP16 Performance | 20.3 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 20.3 TFLOPS | 48.7 TFLOPS |
| Memory Bandwidth | 448 GB/s | 717 GB/s |
Performance Analysis
The RTX 4080 demonstrates superior raw compute capability over the RTX 3070, with 48.7 TFLOPS in FP16 and FP32 compared to 20.3 TFLOPS, representing a 2.4 times increase. This delta translates to faster model training and inference in deep learning pipelines, where FP16 mixed precision accelerates matrix operations without significant accuracy loss. For training large neural networks, the RTX 4080 processes iterations roughly 2.4 times quicker, reducing wall-clock time on equivalent batch sizes.
Memory specifications further favor the RTX 4080: 16 GB GDDR6X VRAM supports larger models or bigger batch sizes than the RTX 3070's 8 GB GDDR6, preventing out-of-memory errors in tasks like transformer training. The 717 GB/s bandwidth, 60% higher than 448 GB/s, minimizes data transfer delays, allowing sustained high throughput during inference on high-resolution inputs. Smaller batch sizes on the RTX 3070 may be necessary, potentially increasing overhead.
Power consumption reflects these gains, with the RTX 4080's 320W TDP exceeding the RTX 3070's 220W by 45%, implying higher operational costs in prolonged cloud sessions but justified by performance uplift.
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 3070
The RTX 3070 suits budget-conscious users running lightweight machine learning workloads. Its 8 GB VRAM handles small to medium models effectively, such as fine-tuning compact LLMs or basic inference, at cloud pricing from $0.04/hr averaging $0.08/hr across 6 offers. Lower 220W TDP also reduces energy costs for intermittent tasks.
Choose the RTX 3070 for prototyping or development where 20.3 TFLOPS suffices and 448 GB/s bandwidth supports modest batch sizes, prioritizing cost over peak performance.
When to Choose the RTX 4080
Opt for the RTX 4080 in performance-intensive scenarios demanding high throughput. Its 48.7 TFLOPS FP16/FP32 and 16 GB VRAM excel in training or inferring large models, accommodating bigger batches without memory constraints. The 717 GB/s bandwidth ensures efficient data handling despite higher average pricing of $0.28/hr.
The RTX 4080 fits production deployments or complex simulations where 2.4 times the compute power justifies the 320W TDP and elevated costs.
Use Cases
LLM training demands substantial VRAM and FP16 performance: the RTX 4080's 16 GB and 48.7 TFLOPS handle larger batches and models better than the RTX 3070's 8 GB and 20.3 TFLOPS.
High inference throughput benefits from elevated bandwidth and compute: RTX 4080's 717 GB/s and 48.7 TFLOPS support more concurrent requests than RTX 3070's 448 GB/s and 20.3 TFLOPS.
Fine-tuning smaller models fits both GPUs, but RTX 3070's lower $0.08/hr average suits experimentation while RTX 4080's 16 GB aids larger adapters.
Image generation requires ample VRAM for high-resolution outputs: RTX 4080's 16 GB GDDR6X outperforms RTX 3070's 8 GB, reducing swapping.
Many simulations fit within 8 GB VRAM and leverage 20.3 TFLOPS FP32 at RTX 3070's cost-effective $0.04/hr starting price.
Frequently Asked Questions
Which GPU has more VRAM: RTX 3070 or RTX 4080?▾
The RTX 4080 provides 16 GB GDDR6X VRAM, double the RTX 3070's 8 GB GDDR6. This allows the RTX 4080 to manage larger models or datasets. Memory bandwidth also differs: 717 GB/s for RTX 4080 versus 448 GB/s.
Is the RTX 4080 faster than the RTX 3070?▾
Yes, the RTX 4080 achieves 48.7 TFLOPS in FP16 and FP32, 2.4 times the RTX 3070's 20.3 TFLOPS. This speedup applies to training and inference tasks. The Ada Lovelace architecture from 2022 contributes to these gains over Ampere in 2020.
What are the cloud rental prices for these GPUs?▾
RTX 3070 rentals start from $0.04/hr, averaging $0.08/hr across 6 offers. RTX 4080 begins at $0.11/hr, averaging $0.28/hr across 8 offers. Prices reflect live cloud provider listings.
RTX 3070 vs RTX 4080 power consumption?▾
The RTX 3070 has a 220W TDP, lower than the RTX 4080's 320W by 45%. Lower TDP means reduced electricity costs for the RTX 3070 in cloud usage. Both use PCIe form factors.
Can RTX 3070 handle large language models?▾
RTX 3070's 8 GB VRAM limits it to smaller LLMs or reduced batch sizes. RTX 4080's 16 GB supports fuller models at 48.7 TFLOPS. For demanding LLMs, RTX 4080 is preferable.
What architectures do these GPUs use?▾
RTX 3070 employs Ampere from 2020, while RTX 4080 uses Ada Lovelace from 2022. Architecture differences yield higher performance metrics for RTX 4080 across FP16, FP32, and bandwidth.
Which is cheaper to rent, the RTX 3070 or the RTX 4080?▾
Cloud rental prices for both the RTX 3070 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 3070 have compared to the RTX 4080?▾
The RTX 3070 has 8 GB of GDDR6 memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find RTX 3070 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 3070 and the RTX 4080?▾
The RTX 3070 uses the Ampere architecture (2020) while the RTX 4080 uses Ada Lovelace (2022). The RTX 4080 delivers 2.4x the FP16 throughput and 1.6x the memory bandwidth of the RTX 3070.