What is the difference between NVIDIA L40 and L40S GPUs?

NVIDIA L40 vs. L40S GPUs: Key Differences Explained

When considering high-performance GPUs for AI training, deployment, and professional visualization workloads, NVIDIA's L40 and L40S GPUs stand out prominently. While both belong to NVIDIA's professional GPU lineup, they differ significantly in key aspects such as specifications, target use cases, and performance capabilities. Below, we outline the primary differences between NVIDIA L40 and L40S GPUs to help you make an informed decision.

1. NVIDIA L40 GPU Overview

The NVIDIA L40 GPU is designed primarily for professional graphics, visualization, and AI inference workloads. It leverages NVIDIA's Ada Lovelace GPU architecture optimized for high-quality rendering, real-time visualization, and moderate AI inference tasks.

Key Specifications (NVIDIA L40):

• Architecture: Ada Lovelace
• CUDA Cores: 18,176
• Tensor Cores: 568 (Fourth-generation Tensor cores)
• Memory Capacity: 48 GB GDDR6
• Memory Bandwidth: 864 GB/s
• FP32 Performance (Single Precision): Approximately 90 TFLOPS
• FP16 Tensor Core Performance: Approximately 360 TFLOPS
• Use Cases: Professional visualization, graphics rendering, AI inference, virtual workstation deployments, and media streaming

2. NVIDIA L40S GPU Overview

The NVIDIA L40S GPU, announced more recently, is specifically tailored to accelerate large-scale generative AI training, high-performance AI inference, and demanding data science workloads. It also utilizes NVIDIA’s Ada Lovelace architecture but is optimized further for intensive generative AI tasks and large model training.

Key Specifications (NVIDIA L40S):

• Architecture: Ada Lovelace
• CUDA Cores: 18,176
• Tensor Cores: 568 (Fourth-generation Tensor cores)
• Memory Capacity: 48 GB GDDR6
• Memory Bandwidth: 864 GB/s
• FP32 Performance (Single Precision): Approximately 90 TFLOPS
• FP16 Tensor Core Performance: Approximately 360 TFLOPS
• Optimized For: Generative AI workloads, Large Language Models (LLMs), AI training, multi-node scalability, and data-center scale deployments
• Enhanced Support: Optimized drivers, software stack, and frameworks specifically targeting generative AI models, e.g., GPT, Stable Diffusion, and generative image/video creation workflows

3. Primary Differences Between NVIDIA L40 and L40S GPUs

Target Use Cases & Optimization

• NVIDIA L40: Primarily optimized for professional graphics, visualization, virtual desktops, real-time rendering, and moderate AI inference workloads.
• NVIDIA L40S: Optimized specifically for large-scale generative AI training, AI inference at scale, and data center AI workloads, with enhanced software stack and driver support specifically tailored for generative AI models.

Software Stack and Support

• NVIDIA L40: Standard support for professional graphics drivers, virtualization solutions (NVIDIA vGPU), and AI inference stacks.
• NVIDIA L40S: Enhanced software stack and optimized driver support specifically aimed at generative AI training workloads, deep learning frameworks (TensorFlow, PyTorch), and large-scale AI infrastructure integration.

Performance and Scalability for AI Workloads

• NVIDIA L40: Delivers strong inference and graphics performance, but may not achieve optimal performance and scalability for large-scale generative AI model training.
• NVIDIA L40S: Specifically tuned for maximizing performance, scalability, and efficiency in AI training tasks involving large models, multi-node setups, and generative AI workflows.

4. Choosing Between NVIDIA L40 and L40S GPUs: Recommendations

• Choose NVIDIA L40 if:

  • Your primary workload is professional graphics rendering, visualization, virtual workstation deployments, or moderate AI inference.
  • Your infrastructure prioritizes graphical workloads, real-time rendering, video streaming, and interactive visualization.

• Choose NVIDIA L40S if:

  • Your workloads are heavily focused on generative AI, large-scale AI model training, or demanding deep learning inference tasks.
  • You require optimized drivers, software stacks, and scalability for generative AI model training (e.g., GPT, diffusion models, large language models).

5. Summary Comparison Table: NVIDIA L40 vs. L40S GPUs

Conclusion

While NVIDIA L40 and L40S GPUs share similar hardware specifications, their primary difference lies in optimization and targeted workloads. The L40 GPU is ideal for professional visualization, graphics-intensive workloads, and moderate AI inference. Conversely, the NVIDIA L40S GPU is specifically optimized for generative AI workloads, intensive AI training, and large-scale deployment scenarios, making it the preferred choice for enterprises focused on AI and deep learning applications.