NVIDIA GeForce RTX 4090 VS NVIDIA GeForce RTX 3080
Choosing between **RTX 4090** and **RTX 3080** depends on your specific AI workload requirements. The **RTX 4090** 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 **$0.18/h** and **$0.10/h** respectively across 14 providers.
RTX 4090
📊 Detailed Specifications Comparison
| Specification | RTX 4090 | RTX 3080 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ada Lovelace | Ampere | - |
| Process Node | 4nm | 8nm | - |
| Target Market | consumer | consumer | - |
| Form Factor | 3-slot PCIe | 2-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 24GB | 10GB | +140% |
| Memory Type | GDDR6X | GDDR6X | - |
| Memory Bandwidth | 1.01 TB/s | 760 GB/s | +33% |
| Memory Bus Width | 384-bit | 320-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 16,384 | 8,704 | +88% |
| Tensor Cores (AI) | 512 | N/A | |
| RT Cores (Ray Tracing) | 128 | N/A | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 82.58 TFLOPS | 29.8 TFLOPS | +177% |
| FP16 (Half Precision) | 165.15 TFLOPS | N/A | |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 450W | 320W | +41% |
| PCIe Interface | PCIe 4.0 x16 | PCIe 4.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA GeForce RTX 4090
Higher VRAM capacity and memory bandwidth are critical for training large language models. The RTX 4090 offers 24GB compared to 10GB.
AI Inference
NVIDIA GeForce RTX 4090
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA GeForce RTX 3080
Based on current cloud pricing, the RTX 3080 starts at a lower hourly rate.
Technical Deep Dive: RTX 4090 vs RTX 3080
This is a generational comparison within the NVIDIA ecosystem, pitting Ada Lovelace against Ampere. The RTX 4090 has a significant **14GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **RTX 3080** is currently about **44% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA GeForce RTX 4090 is Best For:
- Image generation
- AI development
- Enterprise production
NVIDIA GeForce RTX 3080 is Best For:
- Gaming
- Cloud PCs
- VRAM-intensive models
Frequently Asked Questions
Which GPU is better for AI training: RTX 4090 or RTX 3080?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The RTX 4090 offers 24GB of GDDR6X memory with 1.01 TB/s bandwidth, while the RTX 3080 provides 10GB of GDDR6X with 760 GB/s bandwidth. For larger models, the RTX 4090's higher VRAM capacity gives it an advantage.
What is the price difference between RTX 4090 and RTX 3080 in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, RTX 4090 starts at $0.18/hour while RTX 3080 starts at $0.10/hour. This represents a 80% price difference.
Can I use RTX 3080 instead of RTX 4090 for my workload?
It depends on your specific requirements. If your model fits within 10GB of VRAM and you don't need the additional throughput of the RTX 4090, the RTX 3080 can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the RTX 4090's architecture may be essential.
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