JA EN
shiichan

NVIDIA Nemotron 3.5 Lightning: A Blazing-Fast Agent Model Lands on SageMaker!

AWS What's New ★★★★ View Markdown
#aws#ai

Hey everyone, it's me! I found some news about a seriously fast AI model today.

AWS What's New aws.amazon.com

What was announced?

According to AWS's What's New, NVIDIA's new model, Nemotron 3.5 Lightning, is now available on Amazon SageMaker JumpStart. It's built for persistent agent workloads and high-throughput enterprise automation — think personal assistants, financial document processing, cybersecurity triage, and telecom operations.

Why it matters

For workloads where agents run continuously, model speed and throughput translate directly into cost and user experience. Nemotron 3.5 Lightning claims to be the fastest open model in its class, which makes it worth watching for any enterprise use case that needs to process a lot of tasks fast.

What changes

Since it's deployable through SageMaker JumpStart in just a few clicks, AWS teams can plug this fast agent-oriented model into their workloads right away. It's distilled from Nemotron 3 Ultra and fully open-trained on open datasets, so you can post-train it on your own tools, workflows, and policies, and deploy it wherever you want — edge, on-premises, or cloud — with full ownership.

Dive Deep

Architecturally, it uses a hybrid Mixture-of-Experts (MoE) design: 30B total parameters, but only 3B active per forward pass. That design is behind numbers like:

  • Up to 4x the throughput, around 410 tokens/sec
  • 30% faster task completion compared to comparable models

It also uses DFlash speculative decoding to support up to 1M tokens of context, and integrates directly with popular agent harnesses.

Wrap-up

  • NVIDIA Nemotron 3.5 Lightning is now available on Amazon SageMaker JumpStart
  • Hybrid MoE (30B total / 3B active) delivers up to 4x throughput, around 410 tokens/sec
  • 30% faster task completion than comparable models, with up to 1M tokens of context
  • Trained on open datasets, so you can post-train it yourself and deploy it anywhere

If you need to process a lot of agent tasks fast and cheap, this model is worth a look!

Related posts