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[ARTICLE · art-93504] src=build.nvidia.com ↗ pub= topic=artificial-intelligence verified=true sentiment=· neutral

Nemotron-3.5-lightning-30B-a3B Model by Nvidia for use on 1 GPU

Nvidia released the Nemotron-3.5-lightning-30B-a3B model, a 30-billion-parameter AI model with 3 billion active parameters, designed to run on a single GPU. The model is available via Nvidia's NIM API, supporting a context length of 128,000 tokens and a maximum output of 16,384 tokens, with features like reasoning and thinking enabled. It is part of Nvidia's push to provide efficient, high-performance models for enterprise AI applications.

read1 min views2 publishedAug 12, 2026
Nemotron-3.5-lightning-30B-a3B Model by Nvidia for use on 1 GPU
Image: source

Skip to main content Explore Models Skills Blueprints GPUs Docs Search ⌘K Ctrl+K ? Help Center Getting Started 1 Set up your account Create and verify your account to unlock full access to NVIDIA NIM APIs. Create an Account 2 Generate API Key 3 Make your first API call 4 Prototype in your environment 5 Connect to inference partners Resources Developer Forums Contact Support FAQs Login nemotron-3.5-lightning-30b-a3b Model by NVIDIA | NVIDIA NIM nvidia / nemotron-3.5-lightning-30b-a3b Build Build Playground Playground Model Card Model Card API Reference Prototype Start building with a free API endpoint. Python LangChain Node Shell Generate API Key Copied

from openai import OpenAI

client = OpenAI(
  base_url = "https://integrate.api.nvidia.com/v1",
  api_key = "$NVIDIA_API_KEY"
)

completion = client.chat.completions.create(
  model="nvidia/nemotron-3.5-lightning-30b-a3b",
  messages=[{"role":"user","content":""}],
  temperature=1,
  top_p=0.95,
  max_tokens=16384,
  extra_body={"chat_template_kwargs":{"enable_thinking":True},"reasoning_budget":16384},
  stream=True
)

for chunk in completion:
  if not chunk.choices:
    continue
  reasoning = getattr(chunk.choices[0].delta, "reasoning_content", None)
  if reasoning:
    print(reasoning, end="")
  if chunk.choices[0].delta.content is not None:
    print(chunk.choices[0].delta.content, end="")

Deploy Ready to scale? Choose your deployment path. Partner Endpoints Self-Hosted Deployments Available Integrations Deploy this model now on your endpoint provider of choice

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