NVIDIA B200 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 based on demand, from single GPU instances to multi-GPU clusters, with features like low-latency networking and high-speed interconnects. Security measures, compliance certifications, and technical support are standard offerings. Pricing models are usage-based, with costs varying by GPU type, usage duration, and resource allocation.

About the NVIDIA B200

The NVIDIA B200 delivers exceptional AI computing power with 192GB of advanced memory architecture that makes data processing highly efficient. It provides roughly 15 times better inference performance and 3 times better training performance compared to the H100. This performance jump is significant, though it requires robust cooling infrastructure due to higher power consumption.

AI researchers working with large language models and machine learning engineers running massive inference workloads benefit most from the B200. Organizations conducting cutting-edge AI research, companies building AI products serving millions of users, and scientific computing teams handling complex simulations find particular value. The combination of enormous memory capacity and raw computational power makes it ideal for training the largest models and running inference at unprecedented scale.

About the NVIDIA L40

The NVIDIA L40 handles both AI workloads and graphics tasks with 48GB of memory and around 362 TFLOPs of performance. It's optimized for running AI models rather than training them from scratch, focusing on efficiency and lower power consumption. The design targets inference work where you use trained models to generate content or make predictions.

Organizations working with generative AI applications, computer vision systems, and virtual environments choose the L40. Content creators, media companies, and businesses deploying AI-powered services find it useful because it handles both AI processing and visual rendering. While large-scale model training teams might need more memory bandwidth, the L40 works well for companies deploying AI applications in production environments where power efficiency matters.

Comparison

• The NVIDIA B200 offers exceptional performance with 192GB HBM3e memory and up to 15x inference improvement over H100, making it ideal for demanding AI training and HPC workloads. However, it requires pricing on request and has higher power consumption that necessitates robust cooling infrastructure.
• The NVIDIA L40 provides a more accessible entry point at ~$11,000 with solid inference capabilities and lower power consumption, making it suitable for generative AI and graphics workloads. Its 48GB GDDR6 memory and lower bandwidth make it less optimal for large-scale training compared to high-end alternatives.

The NVIDIA B200 suits enterprise organizations and research institutions with substantial budgets and infrastructure requirements who need maximum performance for large-scale AI training and complex HPC workloads. Its advanced architecture and massive memory capacity work best for cutting-edge AI research and production deployments where performance outweighs cost considerations.

The NVIDIA L40 serves organizations and developers seeking balance between capability and affordability, particularly those focused on inference workloads, generative AI applications, and mixed graphics/AI use cases. Its transparent pricing and lower operational requirements make it accessible to smaller teams, startups, and businesses that need solid AI performance without enterprise-grade infrastructure overhead.

FAQ

Q. What is the pricing for NVIDIA B200 and L40 GPUs?

A. The NVIDIA B200 is available on a pricing-on-request basis for retail purchase, with rental starting at $2.40 per hour. The NVIDIA L40 costs approximately $11,000 retail and around $1.00 per hour for rental.

Q. How much memory do these GPUs have?

A. The NVIDIA B200 features 192 GB of HBM3e memory, while the NVIDIA L40 has 48 GB of GDDR6 memory.

Q. What are the best use cases for each GPU?

A. The NVIDIA B200 is optimized for high-performance AI training and inference, as well as HPC tasks. The NVIDIA L40 is best suited for inference workloads in generative AI, vision models, and virtual environments.

Q. What performance advantages does the B200 offer over the H100?

A. The NVIDIA B200 delivers up to 15x better inference performance and 3x better training performance compared to the H100, with an advanced memory architecture that enhances data processing efficiency.

Q. What are the main limitations of each GPU?

A. The NVIDIA B200 has higher power consumption that may require robust cooling solutions. The NVIDIA L40, while optimized for AI and graphics with lower power draw, is less ideal for full-scale training due to lower memory bandwidth compared to high-end training GPUs.

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