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Nvidia Nemotron 3 Super 120B Thinking

nvidia/nemotron-3-super-120b-a12b:thinking
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Nvidia Nemotron 3 Super 120B Thinking

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

Nvidia Nemotron 3 Super 120B with reasoning content enabled. Returns separate thinking content when requested.

Added Mar 1, 2026

Model weights

Context Window

262.1K

Max Output

16.4K

Avg output tokens (7d)

769 tokens

60%

Input Price (Auto)

$0.050/1M

Output Price (Auto)

$0.25/1M

Cache Read (Auto)

$0.025/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

13.6

Better than 55% of models compared

Coding Index

37.7

Better than 44% of models compared

Agentic Index

4.1

Better than 31% of models compared

Agentic work

AutomationBench-AA

Workflow automation with guardrail penalties

3.8%

Better than 29% of models compared

AA-Briefcase

Agentic knowledge work (Elo)

0 Elo

Better than 2% of models compared

GDPval-AA v2

Economically valuable tasks (Elo)

644 Elo

Better than 29% of models compared

Document reasoning

GDP.pdf

Professional PDF reasoning: all-pass rate

2.6%

Better than 21% of models compared

AA-LCR v1.1

Long context reasoning with updated grading

65.7%

Better than 61% of models compared

Reasoning

HLE

Humanity's Last Exam

20.8%

Better than 72% of models compared

IFBench

Instruction-following benchmark

71.5%

Better than 88% of models compared

CritPt

Research-level physics reasoning

3.1%

Coding

Terminal-Bench v4.0

Practical coding and terminal tasks

0.0%

Better than 17% of models compared

SciCode

Python programming for scientific computing

36.2%

Better than 17% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

24.3%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

87.0%

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

80.0%

Better than 67% of models compared

Terminal-Bench Hard (legacy)

Agentic coding and terminal use

28.8%

Better than 71% of models compared

T²-Bench Telecom (legacy)

Conversational AI agents in dual-control scenarios

67.8%

Better than 61% of models compared

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

65.7%

Better than 61% of models compared

GDPval-AA (unversioned / legacy)

Economically valuable tasks

7.2%

Last updated Sep 13, 2026

Artificial Analysis

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