NVIDIA GeForce RTX 4070 VS NVIDIA GeForce RTX 4080
Choosing between **RTX 4070** and **RTX 4080** depends on your specific AI workload requirements. The **RTX 4080** leads in both memory capacity and raw compute power, making it a stronger choice for high-end LLM training. Currently, you can rent these GPUs starting from **$0.11/h** and **$0.13/h** respectively across 3 providers.
📊 Detailed Specifications Comparison
| Specification | RTX 4070 | RTX 4080 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ada Lovelace | Ada Lovelace | - |
| Process Node | 4nm | 4nm | - |
| Target Market | consumer | consumer | - |
| Form Factor | 2-slot PCIe | 3-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 12GB | 16GB | -25% |
| Memory Type | GDDR6X | GDDR6X | - |
| Memory Bandwidth | 504 GB/s | 717 GB/s | -30% |
| Memory Bus Width | 192-bit | 256-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 5,888 | 9,728 | -39% |
| Tensor Cores (AI) | 184 | 304 | -39% |
| RT Cores (Ray Tracing) | 46 | 76 | -39% |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 29.1 TFLOPS | 48.7 TFLOPS | -40% |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 200W | 320W | -38% |
| 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 12GB.
AI Inference
NVIDIA GeForce RTX 4080
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
Based on current cloud pricing, the RTX 4070 starts at a lower hourly rate.
Technical Deep Dive: RTX 4070 vs RTX 4080
Both GPUs utilize the NVIDIA Ada Lovelace architecture. The primary difference lies in their memory capacity and compute core counts. From a cost perspective, the **RTX 4070** is currently about **15% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA GeForce RTX 4070 is Best For:
- Mid-range AI tasks
- Gaming
- Large model 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 or RTX 4080?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The RTX 4070 offers 12GB of GDDR6X memory with 504 GB/s bandwidth, while the RTX 4080 provides 16GB of GDDR6X with 717 GB/s bandwidth. For larger models, the RTX 4080's higher VRAM capacity gives it an advantage.
What is the price difference between RTX 4070 and RTX 4080 in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, RTX 4070 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 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, the RTX 4080 can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the RTX 4070's architecture may be essential.
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