Source: https://ailoot.ai/models/en/nvidia-nemotron-3-super-120b-a12b-u003a-free/
Canonical: https://ailoot.ai/models/en/nvidia-nemotron-3-super-120b-a12b-u003a-free/
Language: en

# NVIDIA: Nemotron 3 Super (free)

[Markdown](https://ailoot.ai/models/en/nvidia-nemotron-3-super-120b-a12b-u003a-free/index.md) · [JSON](https://ailoot.ai/models/en/nvidia-nemotron-3-super-120b-a12b-u003a-free/facts.json)

## [NVIDIA: Nemotron 3 Super (free)](https://ailoot.ai/models/en/nvidia-nemotron-3-super-120b-a12b-u003a-free/)

NVIDIA Nemotron 3 Super is a text reasoning and chat model with 120B total and 12B active parameters. It is designed for collaborative agents, high-volume tasks such as IT ticket processing, tool use and RAG, with thinking, direct-answer and low-effort reasoning modes documented by NVIDIA.

- [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `nvidia/nemotron-3-super-120b-a12b:free`](https://ailoot.ai/models/en/nvidia-nemotron-3-super-120b-a12b-u003a-free/#method-0)
- [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `nvidia/nemotron-3-super-120b-a12b:free`](https://ailoot.ai/models/en/nvidia-nemotron-3-super-120b-a12b-u003a-free/#method-1)

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

NVIDIA Nemotron 3 Super is a general-purpose reasoning and chat model designed for collaborative agents and high-volume workflows, including IT ticket automation. It has 120B total parameters and activates 12B. Its hybrid architecture combines Mamba-2, attention and Latent Mixture-of-Experts layers. Multi-Token Prediction layers add a mechanism for predicting future tokens and support NVIDIA’s native speculative-decoding recipes.

The model accepts text and returns text, including explanations, drafted responses, code and tool-call requests in an appropriate tool-connected application. Its intended uses include agents, chatbots, retrieval-augmented generation, complex instruction following and long-context reasoning. A useful prompt defines the desired artifact and the conditions that govern it. For example: “Classify this incident using the supplied policy, explain the priority from the evidence, draft a reply and list the missing facts required before recommending a fix.”

For IT ticket processing, provide the ticket text, relevant history, environment details and the applicable routing or escalation rules. Ask for separate fields for observed symptoms, likely causes, proposed checks and the reply to the user. The distinction prevents a hypothesis from being recorded as a confirmed diagnosis. If a diagnostic tool runs, feed its actual result into the conversation before asking for a next step. A completed ticket summary should say what was observed and resolved, and which question remains open.

For RAG and knowledge-base work, label the retrieved passages and state whether the model should answer only from them. Request the answer with supporting source references and any conflict between the materials. A practical example is: “Compare these runbook sections, identify the steps that apply to the supplied environment, and return an ordered procedure with a check after each important step.” Preserve versions and conditions from the source; a clear procedure can still be wrong if it combines instructions for incompatible environments.

For collaborative agent tasks, give each stage a clear objective and preserve useful intermediate results. Super is intended to reason over tool observations and maintain a multi-step conversation. The surrounding application executes the tools and keeps the task state. Ask the model to explain what a new observation changes, retain earlier findings that still hold, and distinguish a proposed action from a recorded result. For coding, supply the relevant files and expected behavior, then request revised code, a change explanation and the cases needed to verify it.

NVIDIA documents thinking enabled by default and a direct-answer mode with thinking disabled through the chat template. Super also has a low-effort reasoning option, which uses fewer reasoning tokens than full thinking and is suggested as a starting point before explicit budget tuning. This is the Super setting; Ultra’s separate medium-effort option should not be copied into it. Select a final response form and leave room for that response after reasoning, especially when a tool result or a complex source comparison needs an explanation.

The model supports up to a 1M-token context, while the maker’s Hugging Face configuration defaults to 256K because longer context requires more memory. For long inputs, work within the applicable configuration, keep document boundaries and source labels, and reserve response space. Ask for the relationship to trace across the material rather than an undirected summary of everything. A model-level maximum is not a promise that every serving configuration uses the same window.

The maker lists English, French, German, Italian, Japanese, Spanish and Chinese. Specify the final language while retaining code identifiers and source terms that must stay exact. For multilingual support work, ask the model to preserve the technical meaning and escalation criteria while adapting the wording for the reader. Review unfamiliar terminology or ambiguous input instead of treating fluency as evidence that the interpretation is correct.

A useful final deliverable is compact and checkable: the answer or revised artifact, the observations supporting it, the assumptions and the remaining work. For generated procedures, inspect the checks against the actual environment. For code, compare proposed changes with observed behavior. For a source-based answer, confirm that the cited passage supports the statement. Super’s reasoning and agent training help organize this work; the actual result is established by the material and execution records used to inspect it.

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `nvidia/nemotron-3-super-120b-a12b:free`

[`nvidia/nemotron-3-super-120b-a12b:free`](https://ailoot.ai/models/en/#m=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&route=Ultra&caller=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&fmt=chat)

NVIDIA /`nvidia/nemotron-3-super-120b-a12b:free`

### Overview

NVIDIA Nemotron 3 Super is a text reasoning and chat model with 120B total and 12B active parameters. It is designed for collaborative agents, high-volume tasks such as IT ticket processing, tool use and RAG, with thinking, direct-answer and low-effort reasoning modes documented by NVIDIA.

Accepted inputs

Text

Results

Text

### Available in Ailoot · inputs & methods

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions`

Input types

`text`

Output types

`text`

Context

262,144 tokens

Maximum output

235,929 tokens

Output format

JSON

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`model` | Type`string` | RequirementRequired | Values & limits nvidia/nemotron-3-super-120b-a12b:free | Default— |
| Field`messages` | Type`array` | RequirementRequired | Values & limits | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits false | Defaultfalse |
| Field`max_tokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Maximum: 235,929 | Default— |
| Field`max_completion_tokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Maximum: 235,929 | Default— |
| Field`n` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Maximum: 128 | Default— |
| Field`temperature` | Type`number` | RequirementOptional | Values & limits | Default— |
| Field`top_p` | Type`number` | RequirementOptional | Values & limits | Default— |
| Field`seed` | Type`integer` | RequirementOptional | Values & limits | Default— |
| Field`stop` | Type`` | RequirementOptional | Values & limits | Default— |
| Field`frequency_penalty` | Type`number` | RequirementOptional | Values & limits | Default— |
| Field`presence_penalty` | Type`number` | RequirementOptional | Values & limits | Default— |
| Field`user` | Type`string` | RequirementOptional | Values & limits | Default— |

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractmodel, messages |
| Parameter`optional` | Contractstream, max\_tokens, max\_completion\_tokens, n, temperature, top\_p, seed, stop, frequency\_penalty, presence\_penalty, user |
| Parameter`material_types` | Contracttext |
| Parameter`conditions` | ContractUse literal text messages only. Cache controls, tools, image/audio/video content and streamed responses are unavailable for this method., The complete encoded JSON request must not exceed 262144 bytes. |

Lifecycle: `synchronous_json`

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Standard rate When fast mode is selected

Flex mode

Standard rate When flex mode is selected

Maximum reasoning effort

Standard rate When maximum reasoning effort uses the default adjustment

Explicit cache pricing

Not enabled When explicit cache is requested

Text-only zero rates

Text input and output only. Cache, tools, media and streaming are unavailable. For text-only input and output

#### Ailoot rates

#### Prices by configuration

| Configuration | Rate schedule | Charge |
| --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens **$0** / 1K tokens Output · Output tokens **$0** / 1K tokens Input · Cache read **—** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · OpenAI Chat

curl · create once and retain the complete result

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
export AILOOT_API_KEY
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model": "nvidia/nemotron-3-super-120b-a12b:free", "messages": [{"role": "user", "content": "Summarize the supplied text in three concise points."}], "stream": false}')

Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
# Submit once. Retain the complete result, original identifiers and every response header.
```

### Receive and save results

#### Ailoot Ultra · OpenAI Chat

JSON

##### Keep all completed results

Keep every complete returned response, file and content part.

Retain the complete response, all actual results, original identifiers, usage and response headers.

##### If the original response needs checking

Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.

### Aliases

#### Model aliases

**Ailoot Ultra** [`nvidia/nemotron-3-super-120b-a12b:free`](https://ailoot.ai/models/en/#m=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&route=Ultra&caller=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&fmt=chat)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

[`nvidia/nemotron-3-super-120b-a12b:free`](https://ailoot.ai/models/en/#m=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&route=Ultra&caller=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&fmt=chat)

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `nvidia/nemotron-3-super-120b-a12b:free`

[`nvidia/nemotron-3-super-120b-a12b:free`](https://ailoot.ai/models/en/#m=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&route=Ultra&caller=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&fmt=messages)

NVIDIA /`nvidia/nemotron-3-super-120b-a12b:free`

### Overview

NVIDIA Nemotron 3 Super is a text reasoning and chat model with 120B total and 12B active parameters. It is designed for collaborative agents, high-volume tasks such as IT ticket processing, tool use and RAG, with thinking, direct-answer and low-effort reasoning modes documented by NVIDIA.

Accepted inputs

Text

Results

Text

### Available in Ailoot · inputs & methods

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages`

Input types

`text`

Output types

`text`

Context

262,144 tokens

Maximum output

235,929 tokens

Output format

JSON

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`model` | Type`string` | RequirementRequired | Values & limits nvidia/nemotron-3-super-120b-a12b:free | Default— |
| Field`messages` | Type`array` | RequirementRequired | Values & limits | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits false | Defaultfalse |
| Field`system` | Type`string` | RequirementOptional | Values & limits | Default— |
| Field`max_tokens` | Type`integer` | RequirementRequired | Values & limits Minimum: 1 Maximum: 235,929 | Default— |
| Field`temperature` | Type`number` | RequirementOptional | Values & limits | Default— |
| Field`top_p` | Type`number` | RequirementOptional | Values & limits | Default— |
| Field`top_k` | Type`integer` | RequirementOptional | Values & limits | Default— |
| Field`stop_sequences` | Type`array` | RequirementOptional | Values & limits | Default— |
| Field`metadata` | Type`object` | RequirementOptional | Values & limits | Default— |

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractmodel, messages, max\_tokens |
| Parameter`optional` | Contractstream, system, temperature, top\_p, top\_k, stop\_sequences, metadata |
| Parameter`material_types` | Contracttext |
| Parameter`conditions` | ContractUse literal text messages only. Cache controls, tools, image/audio/video content and streamed responses are unavailable for this method., The complete encoded JSON request must not exceed 262144 bytes. |

Lifecycle: `synchronous_json`

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Standard rate When fast mode is selected

Flex mode

Standard rate When flex mode is selected

Maximum reasoning effort

Standard rate When maximum reasoning effort uses the default adjustment

Text-only zero rates

Text input and output only. Cache, tools, media and streaming are unavailable. For text-only input and output

#### Ailoot rates

#### Prices by configuration

| Configuration | Rate schedule | Charge |
| --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens **$0** / 1K tokens Output · Output tokens **$0** / 1K tokens Input · Cache read **—** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · Anthropic Messages

curl · create once and retain the complete result

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
export AILOOT_API_KEY
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model": "nvidia/nemotron-3-super-120b-a12b:free", "messages": [{"role": "user", "content": "Summarize the supplied text in three concise points."}], "stream": false, "max_tokens": 256}')

Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
# Submit once. Retain the complete result, original identifiers and every response header.
```

### Receive and save results

#### Ailoot Ultra · Anthropic Messages

JSON

##### Keep all completed results

Keep every complete returned response, file and content part.

Retain the complete response, all actual results, original identifiers, usage and response headers.

##### If the original response needs checking

Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.

### Aliases

#### Model aliases

**Ailoot Ultra** [`nvidia/nemotron-3-super-120b-a12b:free`](https://ailoot.ai/models/en/#m=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&route=Ultra&caller=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&fmt=messages)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

[`nvidia/nemotron-3-super-120b-a12b:free`](https://ailoot.ai/models/en/#m=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&route=Ultra&caller=nvidia%2Fnemotron-3-super-120b-a12b%3Afree&fmt=messages)

FAQ · NVIDIA: Nemotron 3 Super (free)

What inputs and results are available?

`POST /v1/chat/completions` · `nvidia/nemotron-3-super-120b-a12b:free`: `text` → `text` `POST /v1/messages` · `nvidia/nemotron-3-super-120b-a12b:free`: `text` → `text`

Which fields does the request use?

`POST /v1/chat/completions` · `nvidia/nemotron-3-super-120b-a12b:free`: `model`, `messages`, `stream`, `max_tokens`, `max_completion_tokens`, `n`, `temperature`, `top_p`, `seed`, `stop`, `frequency_penalty`, `presence_penalty`, `user` `POST /v1/messages` · `nvidia/nemotron-3-super-120b-a12b:free`: `model`, `messages`, `stream`, `system`, `max_tokens`, `temperature`, `top_p`, `top_k`, `stop_sequences`, `metadata`

What limits apply?

`POST /v1/chat/completions` · `nvidia/nemotron-3-super-120b-a12b:free`: `ctx`: `262144`; `max_out`: `235929`; `max_tokens.minimum`: `1`; `max_tokens.maximum`: `235929`; `max_completion_tokens.minimum`: `1`; `max_completion_tokens.maximum`: `235929`; `n.minimum`: `1`; `n.maximum`: `128` `POST /v1/messages` · `nvidia/nemotron-3-super-120b-a12b:free`: `ctx`: `262144`; `max_out`: `235929`; `max_tokens.minimum`: `1`; `max_tokens.maximum`: `235929`

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