Specifications Compared
| Spec | RTX-4080 | RTX-5070 |
|---|---|---|
| TDP | 320W | 250W |
| VRAM | 16 GB | 12 GB |
| CUDA Cores | 9,728 | 6,144 |
| Memory Type | GDDR6X | GDDR7 |
| Architecture | Ada Lovelace | Blackwell |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 304 | 192 |
| FP16 Performance | 48.7 TFLOPS | 40.6 TFLOPS |
| FP32 Performance | 48.7 TFLOPS | 40.6 TFLOPS |
| INT8 Performance | 780 TOPS | 650 TOPS |
| Memory Bandwidth | 717 GB/s | 448 GB/s |
Performance Analysis
The RTX 4080 delivers higher peak compute with 48.7 TFLOPS in FP16 and FP32, surpassing the RTX 5070's 40.6 TFLOPS by approximately 20 percent. This advantage translates to faster model training and inference in half-precision and single-precision workloads, critical for deep learning pipelines. The identical FP16 to FP32 ratio on both GPUs indicates balanced tensor core utilization, but the RTX 4080's edge supports quicker iterations in resource-heavy environments.
Memory bandwidth presents a clear gap: 717 GB/s on the RTX 4080 versus 448 GB/s on the RTX 5070. Higher bandwidth enables larger batch sizes in training, reducing overhead and improving throughput for models like transformers. The RTX 4080's 16 GB VRAM capacity accommodates larger models or datasets without swapping, whereas 12 GB on the RTX 5070 may limit scalability in memory-bound scenarios.
Power efficiency favors the RTX 5070 at 250W TDP against 320W, potentially lowering operational costs in prolonged cloud sessions. The Blackwell architecture introduces GDDR7 memory, which may yield better efficiency per watt despite lower raw specs.
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 4080
The RTX 4080 suits workloads demanding high memory capacity and bandwidth, such as training large language models with batch sizes exceeding typical limits. Its 16 GB VRAM and 717 GB/s bandwidth prevent out-of-memory errors in scenarios where the RTX 5070's 12 GB and 448 GB/s fall short. Users prioritizing 48.7 TFLOPS compute over cost will find the RTX 4080 optimal for rapid prototyping.
Scientific simulations or fine-tuning with extensive datasets benefit from the RTX 4080's superior specs, justifying its average $0.28/hr pricing.
When to Choose the RTX 5070
The RTX 5070 excels in cost-sensitive deployments, offering rentals from $0.08/hr averaging $0.21/hr. Its 250W TDP reduces power costs in extended inference runs, while the Blackwell architecture provides future-proof features like improved ray tracing irrelevant to most ML but beneficial for hybrid tasks.
Light fine-tuning or inference on smaller models leverages the RTX 5070's efficiency without needing the RTX 4080's extra 16 GB VRAM.
Use Cases
The RTX 4080's 16 GB VRAM and 717 GB/s bandwidth support larger batch sizes and models. Its 48.7 TFLOPS exceeds the RTX 5070's 40.6 TFLOPS for faster training.
The RTX 5070's lower $0.08/hr starting price and 250W TDP suit cost-effective, high-volume inference. 12 GB VRAM suffices for most deployed models.
Higher 48.7 TFLOPS and 16 GB VRAM on the RTX 4080 accelerate iterations on parameter-heavy models. Bandwidth of 717 GB/s handles large datasets efficiently.
16 GB VRAM prevents memory constraints during high-resolution image generation. 48.7 TFLOPS ensures quicker diffusion steps than the RTX 5070's 40.6 TFLOPS.
The RTX 4080's superior FP32 performance at 48.7 TFLOPS and 717 GB/s bandwidth excel in simulations. Extra VRAM supports complex datasets.
Frequently Asked Questions
Which GPU has more VRAM?▾
The RTX 4080 provides 16 GB GDDR6X VRAM, exceeding the RTX 5070's 12 GB GDDR7. This difference matters for memory-intensive AI tasks. Bandwidth also favors the RTX 4080 at 717 GB/s over 448 GB/s.
What are the compute performances?▾
Both FP16 and FP32 reach 48.7 TFLOPS on the RTX 4080, compared to 40.6 TFLOPS on the RTX 5070. This gives the RTX 4080 a 20 percent advantage in training and inference. Architectures differ: Ada Lovelace versus Blackwell.
How do cloud prices compare?▾
RTX 5070 rentals start at $0.08/hr with $0.21/hr average across 6 offers. RTX 4080 starts at $0.11/hr averaging $0.28/hr over 8 offers. The RTX 5070 offers better value for lighter workloads.
Which has lower power consumption?▾
The RTX 5070 uses 250W TDP, lower than the RTX 4080's 320W. This reduces costs in power-sensitive cloud environments. Both are PCIe form factors.
Is the RTX 5070 newer?▾
Yes, the RTX 5070 uses 2025 Blackwell architecture, while RTX 4080 is 2022 Ada Lovelace. Newer design may include efficiency gains despite lower peak specs. VRAM types are GDDR7 versus GDDR6X.
Can both handle LLM fine-tuning?▾
The RTX 4080's 16 GB VRAM and 48.7 TFLOPS make it superior for large models. RTX 5070 works for smaller ones at lower $0.21/hr average cost. Bandwidth impacts batch sizes significantly.
Which is cheaper to rent, the RTX 4080 or the RTX 5070?▾
Cloud rental prices for both the RTX 4080 and RTX 5070 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 4080 have compared to the RTX 5070?▾
The RTX 4080 has 16 GB of GDDR6X memory. The RTX 5070 has 12 GB of GDDR7 memory.
Can I find RTX 4080 and RTX 5070 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 4080 and the RTX 5070?▾
The RTX 4080 uses the Ada Lovelace architecture (2022) while the RTX 5070 uses Blackwell (2025). The RTX 4080 delivers 1.2x the FP16 throughput and 1.6x the memory bandwidth of the RTX 5070.