NVIDIA L40S VS NVIDIA A100 80GB
Choosing between **L40S** and **A100 80GB** depends on your specific AI workload requirements. While the **A100 80GB** offers more VRAM for larger models, the **L40S** remains competitive in other areas. Currently, you can rent these GPUs starting from **$0.26/h** and **$0.40/h** respectively across 73 providers.
A100 80GB
📊 Detailed Specifications Comparison
| Specification | L40S | A100 80GB | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ada Lovelace | Ampere | - |
| Process Node | 4nm | 7nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | Dual-slot PCIe | SXM4 / PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 48GB | 80GB | -40% |
| Memory Type | GDDR6 | HBM2e | - |
| Memory Bandwidth | 864 GB/s | 2.0 TB/s | -58% |
| Memory Bus Width | 384-bit | 5120-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 18,176 | 6,912 | +163% |
| Tensor Cores (AI) | 568 | 432 | +31% |
| RT Cores (Ray Tracing) | 142 | N/A | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 91.6 TFLOPS | 19.5 TFLOPS | +370% |
| FP16 (Half Precision) | 183.2 TFLOPS | 312 TFLOPS | -41% |
| TF32 (Tensor Float) | N/A | 156 TFLOPS | |
| FP64 (Double Precision) | N/A | 9.7 TFLOPS | |
| INT8 (Integer Precision) | 733 TOPS | 624 TOPS | +17% |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 350W | 400W | -13% |
| PCIe Interface | PCIe 4.0 x16 | PCIe 4.0 x16 | - |
| Multi-GPU Interconnect | None | NVLink 3.0 (600 GB/s) | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA A100 80GB
Higher VRAM capacity and memory bandwidth are critical for training large language models. The A100 80GB offers 80GB compared to 48GB.
AI Inference
NVIDIA A100 80GB
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA L40S
Based on current cloud pricing, the L40S starts at a lower hourly rate.
Technical Deep Dive: L40S vs A100 80GB
This is a generational comparison within the NVIDIA ecosystem, pitting Ada Lovelace against Ampere. The A100 80GB has a significant **32GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **L40S** is currently about **35% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA L40S is Best For:
- AI inference
- Generative AI
- Maximum memory bandwidth
NVIDIA A100 80GB is Best For:
- AI model training
- Scientific computing
- Newest FP8 precision workloads
Frequently Asked Questions
Which GPU is better for AI training: L40S or A100 80GB?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The L40S offers 48GB of GDDR6 memory with 864 GB/s bandwidth, while the A100 80GB provides 80GB of HBM2e with 2.0 TB/s bandwidth. For larger models, the A100 80GB's higher VRAM capacity gives it an advantage.
What is the price difference between L40S and A100 80GB in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, L40S starts at $0.26/hour while A100 80GB starts at $0.40/hour. This represents a 35% price difference.
Can I use A100 80GB instead of L40S for my workload?
It depends on your specific requirements. If your model fits within 80GB of VRAM and you don't need the additional throughput of the L40S, the A100 80GB can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the L40S's architecture may be essential.
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