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NVIDIA

NVIDIA: Nemotron 3 Super

Access Nemotron 3 Super from NVIDIA using the Puter.js AI API.

Get Started
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms", {
    model: "nvidia/nemotron-3-super-120b-a12b"
}).then(response => {
    document.body.innerHTML = response.message.content;
});
<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms", {
            model: "nvidia/nemotron-3-super-120b-a12b"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

Model Card

Nemotron 3 Super is NVIDIA's open-weight 120B-parameter hybrid Mamba-Transformer MoE model with only 12B active parameters, designed for running complex multi-agent agentic AI systems at scale. It features a 1-million-token context window to prevent goal drift across long tasks and delivers up to 5x higher throughput than its predecessor. The model excels at reasoning, coding, and tool use.

Context Window 262K

tokens

Max Output 262K

tokens

Input Cost $0.1

per million tokens

Output Cost $0.5

per million tokens

Release Date Mar 11, 2026

 

Model Playground

Try Nemotron 3 Super instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat nvidia/nemotron-3-super-120b-a12b
NVIDIA
Chat with Nemotron 3 Super
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Nemotron 3.5 Lightning

Nemotron 3.5 Lightning is a 30B-parameter Mixture-of-Experts model from NVIDIA with 3B active parameters per token, using a hybrid Mamba-2, MoE, and attention layer architecture. It is designed for high-volume, low-latency execution inside multi-agent systems, where a larger reasoning model like Nemotron 3 Ultra plans and delegates, and Lightning handles tool calls, code review, and other repetitive subagent tasks. NVIDIA reports up to 4x higher output throughput than similarly sized open models and, on its PinchBench agent benchmark, 86% accuracy while completing 10,000 tasks 30% faster than Qwen3.6 35B at similar accuracy. The model ships with built-in multi-token prediction and draft models for speculative decoding, and is available in NVFP4 and BF16 checkpoints under the permissive OpenMDW-1.1 license with open weights and training recipes. Choose it for agent harnesses handling frequent, narrow calls, tool validation, or subagent delegation where response speed matters more than broad reasoning depth.

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Nemotron 3 Ultra 550B A55B

Nemotron 3 Ultra 550B A55B is NVIDIA's open-weight frontier reasoning model with 550B total and 55B active parameters, built on a hybrid Mamba-Transformer Mixture-of-Experts architecture. It supports a 1M token context window and is designed for long-running agentic workflows, complex multi-step reasoning, and high-accuracy tasks across code, math, and science. NVIDIA reports up to 5.9x higher inference throughput than comparable open MoE models. On the Artificial Analysis Intelligence Index it scores 48, leading US open-weight models and delivering the highest non-hallucination score in its comparison set (78.7 on AA-Omniscience). Choose it for production agentic pipelines, deep document analysis, or reasoning-heavy API workloads where both accuracy and throughput matter.

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Nemotron 3.5 Content Safety

Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B, designed to moderate both inputs and outputs of LLMs and VLMs. It classifies prompts and responses as safe or unsafe across 23 safety categories based on the Aegis v2 taxonomy, supports 12 languages, and accepts both text and image input. An optional reasoning mode provides step-by-step chain-of-thought traces explaining each decision — useful for auditing and policy tuning. Despite its 4B size, it leads external multimodal safety benchmarks including the top harmful-F1 score on VLGuard, matching or beating 8–12B models. It also supports custom operator-defined content policies enforced at inference time. Choose it for prompt and response moderation pipelines, safety evaluation of LLM outputs, or as an inference-time guardrail in enterprise AI applications requiring explainable, policy-aware content filtering.

Frequently Asked Questions

How do I use Nemotron 3 Super?

You can access Nemotron 3 Super by NVIDIA through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Is Nemotron 3 Super free?

Nemotron 3 Super is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.

What is the pricing for Nemotron 3 Super?
Nemotron 3 Super costs $0.1 per 1M input tokens and $0.5 per 1M output tokens.
Price per 1M tokens
Input$0.1
Output$0.5
Who created Nemotron 3 Super?

Nemotron 3 Super was created by NVIDIA and released on Mar 11, 2026.

What is the context window of Nemotron 3 Super?

Nemotron 3 Super supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.

What is the max output length of Nemotron 3 Super?

Nemotron 3 Super can generate up to 262K tokens in a single response.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Nemotron 3 Super API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

Add Nemotron 3 Super to your app for free

Developers can integrate Nemotron 3 Super for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.

Get started How pricing works