NVIDIA GeForce RTX 4070 Ti SUPER VS NVIDIA GeForce RTX 4080
Choosing between **RTX 4070 Ti Super** and **RTX 4080** depends on your specific AI workload requirements. Currently, you can rent these GPUs starting from **$0.11/h** and **$0.13/h** respectively across 3 providers.
RTX 4070 Ti Super
📊 Detailed Specifications Comparison
| Specification | RTX 4070 Ti Super | RTX 4080 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ada Lovelace | Ada Lovelace | - |
| Process Node | 4nm | 4nm | - |
| Target Market | consumer | consumer | - |
| Form Factor | Dual-slot PCIe | 3-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 16GB | 16GB | |
| Memory Type | GDDR6X | GDDR6X | - |
| Memory Bandwidth | 672 GB/s | 717 GB/s | -6% |
| Memory Bus Width | 256-bit | 256-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 8,448 | 9,728 | -13% |
| Tensor Cores (AI) | 264 | 304 | -13% |
| RT Cores (Ray Tracing) | 66 | 76 | -13% |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 44.1 TFLOPS | 48.7 TFLOPS | -9% |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 285W | 320W | -11% |
| PCIe Interface | PCIe 4.0 x16 | PCIe 4.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA GeForce RTX 4080
Higher VRAM capacity and memory bandwidth are critical for training large language models. The RTX 4080 offers 16GB compared to 16GB.
AI Inference
NVIDIA GeForce RTX 4070 Ti SUPER
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA GeForce RTX 4070 Ti SUPER
Based on current cloud pricing, the RTX 4070 Ti Super starts at a lower hourly rate.
Technical Deep Dive: RTX 4070 Ti Super vs RTX 4080
Both GPUs utilize the NVIDIA Ada Lovelace architecture. The primary difference lies in their compute core counts. From a cost perspective, the **RTX 4070 Ti Super** is currently about **15% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA GeForce RTX 4070 Ti SUPER is Best For:
- AI development
- Gaming
- Enterprise training
NVIDIA GeForce RTX 4080 is Best For:
- Gaming
- AI development
- Budget builds
Frequently Asked Questions
Which GPU is better for AI training: RTX 4070 Ti Super or RTX 4080?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The RTX 4070 Ti Super offers 16GB of GDDR6X memory with 672 GB/s bandwidth, while the RTX 4080 provides 16GB of GDDR6X with 717 GB/s bandwidth. Both GPUs have similar VRAM capacity, so performance characteristics become the deciding factor.
What is the price difference between RTX 4070 Ti Super and RTX 4080 in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, RTX 4070 Ti Super starts at $0.11/hour while RTX 4080 starts at $0.13/hour. This represents a 15% price difference.
Can I use RTX 4080 instead of RTX 4070 Ti Super for my workload?
It depends on your specific requirements. If your model fits within 16GB of VRAM and you don't need the additional throughput of the RTX 4070 Ti Super, the RTX 4080 can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the RTX 4070 Ti Super's architecture may be essential.
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