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nvidia/NVIDIA-Nemotron-3-Super-120B-A12B

NVIDIA Nemotron 3 Super is a hybrid Mixture-of-Experts (MoE) model engineered for highest compute efficiency and accuracy in multi-agent applications and specialized agentic systems. It is optimized to run many collaborating agents per application on a single GPU, delivering high accuracy for reasoning, tool use, and instruction following.

🧠Reasoning🔧Tool calling
Try nvidia/NVIDIA-Nemotron-3-Super-120B-A12BCompareDocs

Specifications

Context window262K tokens
Max output—
API typechat
AddedMay 27, 2026
Model IDdeepinfra/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US
Privacy policyDeepInfra Privacy Policy→

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model — check the base model page or the DeepInfra Inc. models overview.

Pricing

Input / 1M
$0.10
Output / 1M
$0.50
Cache write
—
Cache read
—
Estimated cost
100K input + 10K output$0.0150
1M input + 100K output$0.15
10M input + 1M output$1.50

Requesty charges exactly what the upstream provider charges — no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to deepinfra/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="deepinfra/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

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Frequently asked questions

How much does nvidia/NVIDIA-Nemotron-3-Super-120B-A12B cost?
nvidia/NVIDIA-Nemotron-3-Super-120B-A12B is priced at $0.10 per million input tokens and $0.50 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges — we don't add markup.
What is the context window of nvidia/NVIDIA-Nemotron-3-Super-120B-A12B?
nvidia/NVIDIA-Nemotron-3-Super-120B-A12B has a context window of 262K tokens. That's roughly 350 words of input you can fit in a single prompt.
What can nvidia/NVIDIA-Nemotron-3-Super-120B-A12B do?
nvidia/NVIDIA-Nemotron-3-Super-120B-A12B supports tool calling, extended reasoning. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use nvidia/NVIDIA-Nemotron-3-Super-120B-A12B with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "deepinfra/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B". The Quickstart above shows Python, JavaScript and cURL snippets.

Access nvidia/NVIDIA-Nemotron-3-Super-120B-A12B through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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