Lambda has introduced multi-node NVIDIA HGX B200-accelerated clusters on demand through its 1-Click Clusters service, offering AI engineers and researchers flexible access to cutting-edge infrastructure without long-term contracts. This service provides scalable resources from 16 to 512 nodes connected via NVIDIA Quantum-2 InfiniBand, enabling efficient large-scale AI tasks such as training, fine-tuning, and inference on the latest Blackwell GPUs. By addressing the growing demand for compute power driven by open-source models like DeepSeek R1, Lambda aims to accelerate innovation across industries, supporting agile experimentation and advanced infrastructure access for diverse organizations.
Lambda Announces General Availability of Multi-Node NVIDIA HGX B200-Accelerated Clusters On-Demand
Lambda has introduced the general availability of multi-node NVIDIA HGX B200-accelerated clusters, accessible on-demand through their 1-Click Clusters platform. This offering enables AI engineers and researchers to utilize cutting-edge infrastructure without the constraints of long-term contracts or complex infrastructure management.
The clusters leverage NVIDIA Blackwell GPUs connected via Quantum-2 InfiniBand, providing scalable solutions from 16 to 512 nodes. This setup allows AI teams to efficiently train, fine-tune, and run inference on the latest GPU technology, enhancing their ability to innovate rapidly and experiment with new approaches.
Stephen Balaban, CEO of Lambda, emphasized the importance of immediate access to advanced infrastructure for AI innovation. The platform’s flexibility supports agile experimentation, aligning with the evolving needs of AI projects. Dhanji R. Prasanna, CTO of Block, highlighted their commitment to an open-source approach, underscoring a collaborative effort to share insights and advancements.
In collaboration with NVIDIA, Lambda ensures that organizations across various industries can access these clusters efficiently. This partnership underscores the importance of providing advanced infrastructure to drive AI innovation, reflecting a strategic alignment to meet the growing demands of the field.
Empowering AI Innovation with Flexible
Lambda’s introduction of multi-node NVIDIA HGX B200-accelerated clusters via their 1-Click Clusters platform marks a significant step in providing scalable and flexible infrastructure for AI development. This offering allows AI teams to access up to 512 nodes, each equipped with NVIDIA Blackwell GPUs connected through Quantum-2 InfiniBand, enabling efficient handling of large-scale tasks such as training, fine-tuning, and inference.
The platform’s flexibility is a key feature, allowing users to scale resources according to project needs without the burden of long-term commitments or complex infrastructure management. This scalability ensures that AI teams can adapt quickly to evolving demands, fostering an environment conducive to rapid innovation and experimentation.
By supporting open-source models like DeepSeek R1, Lambda underscores its commitment to collaboration and accessibility in the AI community. The partnership with NVIDIA further enhances this ecosystem, providing robust tools that empower developers to push the boundaries of AI technology effectively.
On-Demand GPU Access
Lambda’s 1-Click Clusters platform offers a scalable solution for accessing multi-node NVIDIA HGX B200-accelerated clusters. This on-demand infrastructure enables AI teams to efficiently train, fine-tune, and run inference using the latest GPU technology, without the constraints of long-term contracts or complex management.
The platform supports up to 512 nodes, each with NVIDIA Blackwell GPUs connected via Quantum-2 InfiniBand. This setup allows for efficient handling of large-scale AI tasks, while maintaining flexibility in resource allocation. Users can scale resources according to project needs, fostering an environment conducive to rapid innovation and experimentation.
Lambda’s collaboration with NVIDIA ensures that organizations across various industries can access these clusters efficiently. Together, they provide advanced infrastructure to drive AI innovation, reflecting a strategic alignment to meet the growing demands of AI development.
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