Nemotron 3.5 Lightning API

NVIDIA Nemotron 3.5 Lightning: free, high-throughput MoE chat model (3B active / 30B total) with 1M-token context, built for agentic workloads and tool calling.

Modalities: TextText
Context window: 1M tokens
Released: Aug 11, 2026

Nemotron 3.5 Lightning overview

Nemotron 3.5 Lightning by NVIDIA

A free, high-throughput MoE model, 3B active parameters out of 30B total, built for agentic workloads and specialized task execution.

Nemotron 3.5 Lightning specs

Model ID: nvidia/nemotron-3.5-lightning
Developer: NVIDIA
Context window: 1,000,000 tokens
Max output: 65,536 tokens
Input: Text
Output: Text
API: OpenAI-compatible, base URL https://api.aimlapi.com/v1

What Is Nemotron 3.5 Lightning?

NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts (MoE) model with 3 billion active parameters out of 30 billion total, built for high-throughput agentic workloads and specialized task execution. It supports a 1,000,000-token context window and returns text output, making it well suited for long-running agent loops, tool-heavy pipelines, and workflows that need to retain large amounts of context without the compute cost of a fully dense model.

Architecture

By activating only 3B of its 30B total parameters per token, Nemotron 3.5 Lightning delivers throughput closer to a small dense model while drawing on a much larger parameter pool, useful for high-volume, latency-sensitive agentic deployments where cost per request matters.

Capabilities

The model supports file input, parallel tool/function calling, streaming responses, and structured outputs, making it a solid fit for agent frameworks and automated pipelines that call external tools and expect predictable, machine-parseable responses.

Use cases

Nemotron 3.5 Lightning is documented as suited to code review, helping specialized agent workflows in software development. It is also documented for tool use, especially as the execution layer in always-on agents that call tools and validate results. Another documented use case is security alert monitoring, where it can enrich alerts, classify incidents, query logs, and prepare findings. It is also described as useful for answering billing questions in high-volume agentic workflows.

Capabilities

Function calling
Streaming
Structured outputs

Nemotron 3.5 Lightning benchmarks by Artificial Analysis

See how Nemotron 3.5 Lightning compares in intelligence, generation speed, cost per task and latency. Data retrieved Nov 3, 2026.

Intelligence#46 / 505.5Index v5.0 Speed#10 / 219293Output tokens / second Cost per task#13 / 44$0.29USD / benchmark task Latency#9 / 2160.57Seconds to first token

Benchmark results

Compare 6 models available on AI/ML API across 5 independent benchmarks.

Humanity's Last Exam

Expert-written questions across academic subjects.

How to use the Nemotron 3.5 Lightning API

View docs

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key

export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/chat/completions' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "nvidia/nemotron-3.5-lightning",
  "messages": [
    {
      "role": "user",
      "content": "Write a haiku about the ocean."
    }
  ]
}'

import os
import requests

headers = {
    "Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
    "Content-Type": "application/json",
}
payload = {
    "model": "nvidia/nemotron-3.5-lightning",
    "messages": [
        {
            "role": "user",
            "content": "Write a haiku about the ocean."
        }
    ]
}

response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())

const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "nvidia/nemotron-3.5-lightning",
    "messages": [
      {
        "role": "user",
        "content": "Write a haiku about the ocean."
      }
    ]
  }),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());

All posts

Nemotron 3.5 Lightning FAQ

What is the context window of Nemotron 3.5 Lightning?

Nemotron 3.5 Lightning has a 1,000,000 tokens context window and can return up to 65,536 tokens.

What inputs and outputs does Nemotron 3.5 Lightning support?

Nemotron 3.5 Lightning takes text as input and returns text.

What is the model ID for Nemotron 3.5 Lightning?

Use nvidia/nemotron-3.5-lightning as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.

When was Nemotron 3.5 Lightning released?

Nemotron 3.5 Lightning became available on August 11, 2026.

How much does Nemotron 3.5 Lightning cost?

Nemotron 3.5 Lightning is priced at input $0 / 1M, output $0 / 1M.

Does Nemotron 3.5 Lightning support streaming?

Yes, Nemotron 3.5 Lightning can stream responses as they are generated.

Who created Nemotron 3.5 Lightning?

Nemotron 3.5 Lightning was built by NVIDIA.

How many parameters does Nemotron 3.5 Lightning have?

It is a mixture-of-experts model with 30B total parameters, using 3B active parameters per task.

Start building with Nemotron 3.5 Lightning

Get API key