NOUMENOpen app
NOUMEN

nvidia · Open weights

Nvidia Nemotron 3 Super 120B

Added Mar 1, 2026Open weights

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

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.

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Nvidia Nemotron 3 Super 120BnvidiaThis modelNvidia Nemotron 3.5 Super VLnvidiaRemove
Providernvidianvidia
Discovery tierOpen weightsOpen weights
AddedMar 1, 2026Oct 15, 2026
Limits
Context window262.14K262.14K
Max output16.38K16.38K
Average output431 tokens1.1K tokens
Pricing, USD per 1M tokens
Input$0.05Best$0.15
Output$0.25Best$0.50
Cache read—$0.02
Performance
Throughput—654.7 tok/s
Time to first token—1.8 s
Request success (24h)99.9%Best98.0%
Benchmark indexes
Intelligence Index12.826.5Best
Coding Index37.7—
Capabilities
ReasoningYesYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
Video inputNoYes
Reasoning effort—none, medium, high

Public evaluations

Benchmarks

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

  • Nvidia Nemotron 3 Super 120B
  • Nvidia Nemotron 3.5 Super VL

Intelligence Index

  • Nvidia Nemotron 3 Super 120B12.8
  • Nvidia Nemotron 3.5 Super VL26.5

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
    • Nvidia Nemotron 3.5 Super VL: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Nvidia Nemotron 3 Super 120B: 3.8%
    • Nvidia Nemotron 3.5 Super VL: 14.8%Top

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Nvidia Nemotron 3 Super 120B: 0.3%
    • Nvidia Nemotron 3.5 Super VL: 2.0%Top

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Nvidia Nemotron 3 Super 120B: —
    • Nvidia Nemotron 3.5 Super VL: 999 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Nvidia Nemotron 3 Super 120B: 490 Elo
    • Nvidia Nemotron 3.5 Super VL: 1,162 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Nvidia Nemotron 3 Super 120B: 2.6%
    • Nvidia Nemotron 3.5 Super VL: 8.0%Top

  • AA-LCRv1.1

    Reasoning across long documents

    • Nvidia Nemotron 3 Super 120B: 65.7%
    • Nvidia Nemotron 3.5 Super VL: 69.0%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • Nvidia Nemotron 3 Super 120B: —
    • Nvidia Nemotron 3.5 Super VL: 13.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Nvidia Nemotron 3 Super 120B: 20.8%
    • Nvidia Nemotron 3.5 Super VL: 30.7%Top

  • GPQA Diamond

    Graduate-level science questions

    • Nvidia Nemotron 3 Super 120B: 80.0%
    • Nvidia Nemotron 3.5 Super VL: —

  • IFBench

    Following precise output instructions

    • Nvidia Nemotron 3 Super 120B: 71.5%
    • Nvidia Nemotron 3.5 Super VL: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Nvidia Nemotron 3 Super 120B: 0.0%Top
    • Nvidia Nemotron 3.5 Super VL: 0.0%Top

  • SciCode

    Scientific computing in Python

    • Nvidia Nemotron 3 Super 120B: 36.2%
    • Nvidia Nemotron 3.5 Super VL: 47.8%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Nvidia Nemotron 3 Super 120B: 28.8%
    • Nvidia Nemotron 3.5 Super VL: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Nvidia Nemotron 3 Super 120B: 67.8%
    • Nvidia Nemotron 3.5 Super VL: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Nvidia Nemotron 3 Super 120B: 65.7%
    • Nvidia Nemotron 3.5 Super VL: 69.0%Top

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.