Specifications Compared
| Spec | RTX-4060 | RTX-4080 |
|---|---|---|
| TDP | 115W | 320W |
| VRAM | 8 GB | 16 GB |
| CUDA Cores | 3,072 | 9,728 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ada Lovelace | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 96 | 304 |
| FP16 Performance | 15.1 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 15.1 TFLOPS | 48.7 TFLOPS |
| INT8 Performance | 242 TOPS | 780 TOPS |
| Memory Bandwidth | 272 GB/s | 717 GB/s |
Performance Analysis
Raw specifications reveal stark differences in compute capacity: the RTX 4080 SUPER delivers 48.7 TFLOPS in FP16 and FP32, over three times the 15.1 TFLOPS of the RTX 4060 Ti. This delta translates to faster model training and inference; training a large language model on the RTX 4080 SUPER completes epochs roughly three times quicker due to higher throughput in half-precision tasks common in deep learning.
Memory bandwidth plays a critical role: 717 GB/s on the RTX 4080 SUPER versus 272 GB/s on the RTX 4060 Ti enables larger batch sizes without bottlenecks. For instance, inference on models exceeding 8 GB VRAM fails on the RTX 4060 Ti, while the RTX 4080 SUPER's 16 GB GDDR6X handles them seamlessly, reducing latency in production deployments.
Power draw underscores efficiency: the RTX 4060 Ti's 115W TDP supports dense clusters with lower cooling needs, but the RTX 4080 SUPER's 320W demands robust infrastructure. These factors position the RTX 4080 SUPER for high-throughput AI pipelines and the RTX 4060 Ti for cost-sensitive prototyping.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4080 SUPER
| 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 4060 Ti
The RTX 4060 Ti excels in budget-constrained environments for lightweight AI inference and fine-tuning small models under 8 GB. Its $0.08 per hour starting price and 115W TDP minimize operational costs for development teams running Stable Diffusion at 15.1 TFLOPS or basic scientific computing tasks. Deploy it for edge-like cloud instances where 272 GB/s bandwidth suffices for modest batch sizes.
When to Choose the RTX 4080 SUPER
Opt for the RTX 4080 SUPER in performance-critical scenarios like LLM training or large-scale inference requiring 16 GB VRAM and 717 GB/s bandwidth. Its 48.7 TFLOPS handles complex workloads three times faster than the RTX 4060 Ti, justifying the $0.17 per hour starting cost for enterprises prioritizing speed over economy.
Use Cases
The RTX 4080 SUPER's 48.7 TFLOPS and 16 GB VRAM support larger models and batch sizes critical for effective training. The RTX 4060 Ti's 8 GB limits scale to smaller datasets only.
Higher 717 GB/s bandwidth on the RTX 4080 SUPER reduces latency for production inference on big models. The RTX 4060 Ti handles small models adequately but bottlenecks on VRAM-intensive queries.
Fine-tuning mid-sized models fits the RTX 4060 Ti's 15.1 TFLOPS and 8 GB VRAM for cost savings at $0.14 per hour average. The RTX 4080 SUPER accelerates larger adaptations with 48.7 TFLOPS.
The RTX 4060 Ti delivers sufficient 15.1 TFLOPS for image generation at low cost ($0.08 per hour start). Its 8 GB VRAM meets typical Stable Diffusion needs without excess power draw.
Complex simulations benefit from the RTX 4080 SUPER's 48.7 TFLOPS FP32 and 717 GB/s bandwidth for high-precision computations. The RTX 4060 Ti suits simpler tasks only.
Frequently Asked Questions
Which GPU has more VRAM: RTX 4060 Ti or RTX 4080 SUPER?▾
The RTX 4080 SUPER provides 16 GB GDDR6X VRAM, double the 8 GB GDDR6 on the RTX 4060 Ti. This allows the RTX 4080 SUPER to load larger models without swapping to system memory.
What is the performance difference in TFLOPS?▾
The RTX 4080 SUPER achieves 48.7 TFLOPS in both FP16 and FP32, compared to 15.1 TFLOPS on the RTX 4060 Ti. This results in over three times faster compute for AI workloads.
How do cloud prices compare?▾
RTX 4060 Ti pricing starts at $0.08 per hour with an average of $0.14 per hour across four offers. RTX 4080 SUPER starts at $0.17 per hour, averaging $0.32 per hour across three offers.
Which has higher memory bandwidth?▾
The RTX 4080 SUPER offers 717 GB/s bandwidth, more than double the RTX 4060 Ti's 272 GB/s. Higher bandwidth supports larger batch sizes in training and inference.
What are the TDP ratings?▾
The RTX 4060 Ti has a 115W TDP, suitable for efficient deployments. The RTX 4080 SUPER requires 320W, demanding more power infrastructure.
Are both GPUs on the same architecture?▾
Yes, both use the Ada Lovelace architecture, with RTX 4060 Ti from 2023 and RTX 4080 SUPER from 2022. They share PCIe form factors for cloud compatibility.
Which is cheaper to rent, the RTX 4060 or the RTX 4080?▾
Cloud rental prices for both the RTX 4060 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 4060 have compared to the RTX 4080?▾
The RTX 4060 has 8 GB of GDDR6 memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find RTX 4060 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 4060 and the RTX 4080?▾
The RTX 4060 uses the Ada Lovelace architecture (2023) while the RTX 4080 uses Ada Lovelace (2022). The RTX 4080 delivers 3.2x the FP16 throughput and 2.6x the memory bandwidth of the RTX 4060.