NVIDIA GB200 NVL72 vs. NVIDIA L40: When to choose which

GPU cloud services deliver high-performance computing capabilities with specialized infrastructure for AI and machine learning workloads. Users get access to GPU clusters connected through high-bandwidth networks, enabling distributed processing and faster model training. These services include pre-configured environments optimized for common AI frameworks, reducing setup time and complexity.

The infrastructure scales on demand, from single GPU instances to multi-GPU clusters, with low-latency networking and high-speed interconnects. Security measures, compliance certifications, and technical support come standard. Pricing follows usage-based models, with costs varying by GPU type, usage duration, and resource allocation.

About the NVIDIA GB200 NVL72

The NVIDIA GB200 NVL72 is a rack-scale system designed for the largest AI models. It combines 36 processors with 72 of NVIDIA's newest graphics chips, all liquid-cooled for optimal performance. The system provides over 13 TB of high-speed memory and runs AI models 30 times faster than previous systems.

This system targets large tech companies and research labs training next-generation AI systems or running massive models. Universities conducting cutting-edge AI research, companies building ChatGPT-style services, and teams working with trillion-parameter models benefit most. These users need real-time performance for the largest possible AI models rather than waiting hours or days for results.

About the NVIDIA L40

The NVIDIA L40 is a specialized GPU combining AI and graphics capabilities, featuring 48 GB of memory and 362 TFLOPs of performance. It excels at running trained AI models rather than training new ones from scratch. The design handles workloads requiring both AI processing and visual rendering power.

Developers working on generative AI applications, computer vision projects, and virtual environments choose the L40. It appeals to teams deploying AI models in production, especially for visual content or immersive experiences. The GPU consumes less power than training-focused alternatives, making it suitable for continuous inference workloads. While not ideal for training massive models, it works well for companies implementing existing AI in real applications.

Comparison

NVIDIA GB200 NVL72: Delivers exceptional performance with up to 1,440 PFLOPs and 13.5 TB memory, ideal for trillion-parameter model inference and massive AI training workloads. However, it requires significant capital investment ($60,000-$70,000) and substantial power/cooling infrastructure suitable only for large data centers.

NVIDIA L40: Offers accessible entry point at $11,000 with solid inference capabilities and 48 GB memory, suitable for generative AI and vision applications. Its lower memory bandwidth and computational power limit effectiveness for large-scale training compared to higher-end alternatives.

The NVIDIA GB200 NVL72 suits large enterprises, cloud service providers, and research institutions needing maximum AI performance with substantial infrastructure budgets. Its rack-scale design and exceptional computational power make it ideal for organizations running the largest language models and conducting cutting-edge AI research at scale.

The NVIDIA L40 serves small to medium businesses, startups, and individual researchers needing solid AI inference capabilities without enterprise-level infrastructure requirements. Its balanced price-to-performance ratio and moderate power consumption make it accessible for organizations deploying generative AI applications, computer vision projects, and mixed AI/graphics workloads in standard server environments.

FAQ

What is the price difference between the NVIDIA GB200 NVL72 and NVIDIA L40?

The NVIDIA GB200 NVL72 costs approximately $60,000–$70,000, while the NVIDIA L40 costs around $11,000. This makes the GB200 NVL72 roughly 5-6 times more expensive than the L40.

How much memory does each system offer?

The NVIDIA GB200 NVL72 offers up to 13.5 TB of HBM3e memory, while the NVIDIA L40 has 48 GB of GDDR6 memory. The GB200 provides significantly more memory capacity for large-scale AI applications.

What are the best use cases for each system?

The NVIDIA GB200 NVL72 is designed for real-time trillion-parameter LLM inference, massive-scale AI training, and energy-efficient HPC. The NVIDIA L40 is optimized for inference for generative AI, vision models, and virtual environments.

What are the key limitations of each system?

The GB200 NVL72 has high acquisition costs and power requirements, making it suitable only for large-scale data centers. The L40 has lower memory bandwidth, making it less ideal for full-scale training workloads.

How do the rental costs compare?

The NVIDIA L40 rents for approximately $1.00 per hour, while the GB200 NVL72 rental pricing is available only on request, likely reflecting its enterprise-scale positioning and significantly higher costs.

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