NVIDIA L4 VS NVIDIA T4G
Choosing between **L4** and **T4G** depends on your specific AI workload requirements. The **L4** 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 **$0.26/h** and **$0.23/h** respectively across 33 providers.
📊 Detailed Specifications Comparison
| Specification | L4 | T4G | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ada Lovelace | Turing | - |
| Process Node | 4nm | 12nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | Single-slot PCIe | AWS Instance | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 24GB | 16GB | +50% |
| Memory Type | GDDR6 | GDDR6 | - |
| Memory Bandwidth | 300 GB/s | 320 GB/s | -6% |
| Memory Bus Width | 192-bit | 256-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 7,424 | 2,560 | +190% |
| Tensor Cores (AI) | 232 | N/A | |
| RT Cores (Ray Tracing) | 58 | N/A | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 30.3 TFLOPS | 8.1 TFLOPS | +274% |
| FP16 (Half Precision) | 121 TFLOPS | N/A | |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 72W | 70W | +3% |
| PCIe Interface | PCIe 4.0 x16 | PCIe 3.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA L4
Higher VRAM capacity and memory bandwidth are critical for training large language models. The L4 offers 24GB compared to 16GB.
AI Inference
NVIDIA L4
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA T4G
Based on current cloud pricing, the T4G starts at a lower hourly rate.
Technical Deep Dive: L4 vs T4G
This is a generational comparison within the NVIDIA ecosystem, pitting Ada Lovelace against Turing. The L4 has a significant **8GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **T4G** is currently about **12% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA L4 is Best For:
- Edge AI inference
- Video transcoding
- Large model training
NVIDIA T4G is Best For:
- ARM-based AI inference
- x86 native workloads
Frequently Asked Questions
Which GPU is better for AI training: L4 or T4G?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The L4 offers 24GB of GDDR6 memory with 300 GB/s bandwidth, while the T4G provides 16GB of GDDR6 with 320 GB/s bandwidth. For larger models, the L4's higher VRAM capacity gives it an advantage.
What is the price difference between L4 and T4G in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, L4 starts at $0.26/hour while T4G starts at $0.23/hour. This represents a 13% price difference.
Can I use T4G instead of L4 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 L4, the T4G can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the L4's architecture may be essential.
Ready to rent a GPU?
Compare live pricing across 50+ cloud providers and find the best deal.