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nvidia-nemotron-3-super-120b-a12b

NVIDIA/Open weights/1 provider

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.More

Which id to call

nvidia-nemotron-3-super-120b-a12b

Requesty routes this id across every provider serving nvidia-nemotron-3-super-120b-a12b, picking on price and health and failing over automatically. The id stays valid when a provider changes underneath it.

From /1M input

$0.07

DeepInfra Inc.

Context

262K

tokens

Endpoints

2

1 region

Price spread

1.5x

2 endpoints

Capabilities 3/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

2 endpoints / 1 region

Providers serving nvidia-nemotron-3-super-120b-a12b

Provider prices, per 1M tokens. Pay as you go adds 5%, or 0% on your own keys.

Providers serving nvidia-nemotron-3-super-120b-a12b, with pricing and measured performance. The best value in each column is highlighted.
RankPrivacy
1DeepInfra Inc.Global262K$0.07$0.32zdr
2DeepInfra Inc.Global262K$0.10$0.50zdr

A column is blank where no qualifying sample exists, and every row links to that provider's endpoint page.

model=

Which id to call

One base url, https://router.requesty.ai/v1, and one key for every id here.

nvidia-nemotron-3-super-120b-a12b

Requesty routes this id across every provider serving nvidia-nemotron-3-super-120b-a12b, picking on price and health and failing over automatically. The id stays valid when a provider changes underneath it.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.

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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="nvidia-nemotron-3-super-120b-a12b", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Artificial Analysis

Benchmark scores

Coding Indexcoding
37.7%

Artificial Analysis Coding Index: a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
80.0%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
12.8%

Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.

Scores from artificialanalysis.ai. They measure the model, not the provider, so they are the same on every endpoint above.

6

More from NVIDIA

Reference

nvidia-nemotron-3-super-120b-a12b questions

Which providers serve nvidia-nemotron-3-super-120b-a12b?

nvidia-nemotron-3-super-120b-a12b is available from 1 provider through Requesty: DeepInfra Inc.. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.

How much does nvidia-nemotron-3-super-120b-a12b cost?

Pricing starts at $0.07 per million input tokens and $0.32 per million output tokens on DeepInfra Inc., the cheapest endpoint. Prices vary by provider and region; the table above shows every endpoint. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

Is nvidia-nemotron-3-super-120b-a12b open weights?

Yes. nvidia-nemotron-3-super-120b-a12b is an open-weights model from NVIDIA, which is why multiple inference providers can host it. Provider choice affects price, latency, and data-privacy terms, all compared above.

What is the context window of nvidia-nemotron-3-super-120b-a12b?

nvidia-nemotron-3-super-120b-a12b supports up to 262K tokens of context. Some providers expose a smaller window; check the per-endpoint context column above.

How do I use 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 "nvidia-nemotron-3-super-120b-a12b" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.

Should I call nvidia-nemotron-3-super-120b-a12b by its managed id or a provider id?

Use the managed id, "nvidia-nemotron-3-super-120b-a12b". Requesty picks which of the 1 provider serves each request based on price and health, and fails over when one degrades, so the id keeps working while the routing changes underneath it. Send a provider id like "deepinfra/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B:flex" only when you need one specific deployment and want no failover.

Route nvidia-nemotron-3-super-120b-a12b through one endpoint

One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in.

Benchmark rankings