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Nvidia Nemotron 3 Super 120B

Added Mar 1, 2026Open weights

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Use in the app

Nvidia's Nemotron 3 Super 120B A12B model from the March 2026 Nemotron 3 release. It uses a hybrid Mamba-Transformer MoE architecture and targets agentic and coding workloads with a 262K context window here.

  • Reasoning
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.05
Output
$0.25

Reference prices as published by the model provider. API example

Specifications

Context window
262.1K
Max output
16.4K
Average output (7 days)
431 tokens
Longer than 43% of 468 models

Side by side

Nvidia Nemotron 3 Super 120B compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Nvidia Nemotron 3 Super 120BnvidiaThis modelKimi K2 0711 FastMoonshotRemove
ProvidernvidiaMoonshot
Discovery tierOpen weightsOpen weights
AddedMar 1, 2026Dec 15, 2025
Limits
Context window262.14KBest131.07K
Max output16.38K16.38K
Average output431 tokens—
Pricing, USD per 1M tokens
Input$0.05Best$0.40
Output$0.25Best$1.80
Performance
Request success (24h)99.9%—
Benchmark indexes
Intelligence Index12.8Best12.7
Coding Index37.7—
Math Index—57.0
Capabilities
ReasoningYesNo
PDF inputNoYes
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Nvidia Nemotron 3 Super 120B
  • Kimi K2 0711 Fast

Intelligence Index

  • Nvidia Nemotron 3 Super 120B12.8
  • Kimi K2 0711 Fast12.7

Nvidia Nemotron 3 Super 120B: Better than 29% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Nvidia Nemotron 3 Super 120B: 37.7
    • Kimi K2 0711 Fast: —

  • Math Index

    Composite of the math evaluations

    • Nvidia Nemotron 3 Super 120B: —
    • Kimi K2 0711 Fast: 57.0

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Nvidia Nemotron 3 Super 120B: 3.8%
    • Kimi K2 0711 Fast: —

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Nvidia Nemotron 3 Super 120B: 0.3%
    • Kimi K2 0711 Fast: —

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Nvidia Nemotron 3 Super 120B: 490 Elo
    • Kimi K2 0711 Fast: —

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Nvidia Nemotron 3 Super 120B: 2.6%
    • Kimi K2 0711 Fast: —

  • AA-LCRv1.1

    Reasoning across long documents

    • Nvidia Nemotron 3 Super 120B: 65.7%Top
    • Kimi K2 0711 Fast: 53.0%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Nvidia Nemotron 3 Super 120B: 20.8%Top
    • Kimi K2 0711 Fast: 7.4%

  • GPQA Diamond

    Graduate-level science questions

    • Nvidia Nemotron 3 Super 120B: 80.0%Top
    • Kimi K2 0711 Fast: 76.6%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Nvidia Nemotron 3 Super 120B: —
    • Kimi K2 0711 Fast: 82.4%

  • IFBench

    Following precise output instructions

    • Nvidia Nemotron 3 Super 120B: 71.5%Top
    • Kimi K2 0711 Fast: 41.5%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Nvidia Nemotron 3 Super 120B: 0.0%
    • Kimi K2 0711 Fast: —

  • SciCode

    Scientific computing in Python

    • Nvidia Nemotron 3 Super 120B: 36.2%
    • Kimi K2 0711 Fast: —

  • LiveCodeBench

    Recent competitive programming problems

    • Nvidia Nemotron 3 Super 120B: —
    • Kimi K2 0711 Fast: 55.6%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Nvidia Nemotron 3 Super 120B: —
    • Kimi K2 0711 Fast: 57.0%

  • AIME

    Competition mathematics

    • Nvidia Nemotron 3 Super 120B: —
    • Kimi K2 0711 Fast: 69.3%

  • MATH-500

    Competition math problems

    • Nvidia Nemotron 3 Super 120B: —
    • Kimi K2 0711 Fast: 97.1%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Nvidia Nemotron 3 Super 120B: 28.8%Top
    • Kimi K2 0711 Fast: 15.9%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Nvidia Nemotron 3 Super 120B: 67.8%Top
    • Kimi K2 0711 Fast: 61.1%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Nvidia Nemotron 3 Super 120B: 65.7%Top
    • Kimi K2 0711 Fast: 53.0%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
1.4%
Request success (24h)
99.9%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 96.4%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nvidia/nemotron-3-super-120b-a12b",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="nvidia/nemotron-3-super-120b-a12b",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

nvidia

Other nvidia models, starting with the same family.