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СпутникиРНSpaceXРоскосмосNASANVIDIA's Nemotron 3.5 Lightning is now available on Amazon SageMaker JumpStart, giving AWS customers access to the fastest open model in its class for persistent agent workloads and rapid task execution.
Nemotron 3.5 Lightning is engineered for persistent agents and high-throughput enterprise automation across domains including personal assistants, financial document processing, cybersecurity triage, and telecom operations. Built on a hybrid Mixture-of-Experts (MoE) architecture with 30B total parameters and just 3B active per forward pass, it achieves up to 4x the throughput (~410 tokens/sec) and 30% faster task completion over comparable models. Distilled from Nemotron 3 Ultra, it handles up to 1M tokens of context via DFlash speculative decoding and integrates directly with popular agent harnesses. The model is fully open-trained on open datasets thereby allowing enterprises to post-train for their own tools, workflows, and policies, and deploy with complete ownership across edge, on-premises, or cloud infrastructure.
With SageMaker JumpStart, customers can deploy this model in a few clicks to power their specific AI workloads.
To get started with these models, navigate to the SageMaker JumpStart model catalog in the SageMaker console or use the SageMaker Python SDK to deploy the models to your AWS account. For more information about deploying and using foundation models in SageMaker JumpStart, see the Amazon SageMaker JumpStart documentation.
NVIDIA's Nemotron 3.5 Lightning is now available on Amazon SageMaker JumpStart, giving AWS customers access to the fastest open model in its class for persistent agent workloads and rapid task execution.
Nemotron 3.5 Lightning is engineered for persistent agents and high-throughput enterprise automation across domains including personal assistants, financial document processing, cybersecurity triage, and telecom operations. Built on a hybrid Mixture-of-Experts (MoE) architecture with 30B total parameters and just 3B active per forward pass, it achieves up to 4x the throughput (~410 tokens/sec) and 30% faster task completion over comparable models. Distilled from Nemotron 3 Ultra, it handles up to 1M tokens of context via DFlash speculative decoding and integrates directly with popular agent harnesses. The model is fully open-trained on open datasets thereby allowing enterprises to post-train for their own tools, workflows, and policies, and deploy with complete ownership across edge, on-premises, or cloud infrastructure.
With SageMaker JumpStart, customers can deploy this model in a few clicks to power their specific AI workloads.
To get started with these models, navigate to the SageMaker JumpStart model catalog in the SageMaker console or use the SageMaker Python SDK to deploy the models to your AWS account. For more information about deploying and using foundation models in SageMaker JumpStart, see the Amazon SageMaker JumpStart documentation.