NVIDIA Nemotron 3 Super

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

Run NVIDIA Nemotron 3 Super in a hosted Python Task with extended thinking and file inputs.

NVIDIA's Nemotron 3 Super via OpenRouter. An open hybrid Mamba-Transformer mixture-of-experts model (120B total, 12B active parameters) for multi-agent work, with a 262K token context window.

What NVIDIA Nemotron 3 Super supports in qbash

Extended thinkingReasons through a problem before it replies.
Reasoning effort2 levels, from low to medium.
Document inputReads PDF, TEXT, DOC, XLS, RTF and 7 more files.

What is qbash?

qbash is where you build Tasks: Python programs that run a business process on managed infrastructure. Your code runs the steps and calls a model like NVIDIA Nemotron 3 Super only at the ones that need judgment, with integrations, memory and files available in the same script.

A developer writes the Task once, and anyone on the team runs it from a form, on a schedule, from a webhook or from chat. Each Task is versioned and every run is logged.

How Tasks work

Specifications

Context window: 262Ktokens
Max output: 16,384tokens
Temperature: 0 to 1default 1

Use NVIDIA Nemotron 3 Super in a Python Task

qbash.ai.raw calls NVIDIA Nemotron 3 Super from a Task and returns its reply as a string.

main.py
notes = qbash.inputs.get("notes")

summary = qbash.ai.raw(
    f"Summarize these meeting notes in five bullets:\n\n{notes}",
    model="nvidia/nemotron-3-super-120b-a12b",
    system="You are a concise analyst.",
)

qbash.output({"summary": summary})

Model calls in Tasks

Reasoning effort with NVIDIA Nemotron 3 Super

Set Effort to low and medium in the prompt's Settings. Higher effort spends more tokens on reasoning before the reply.

Turn on Thinking in the same Settings popover to have NVIDIA Nemotron 3 Super reason through a problem before it replies.