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Nemotron 3.5 Content Safety

Added Sep 19, 2026Open weights

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Nemotron 3.5 Content Safety is a content moderation classifier that labels user messages and assistant responses as safe or unsafe. It supports a 131,072-token context window and optional reasoning.

  • Reasoning
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.05
Output
$0.15
Cache read
$0.025

Reference prices as published by the model provider. API example

Specifications

Context window
131.1K
Max output
32.8K
Average output (7 days)
16 tokens
Longer than 0% of 465 models

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Nemotron 3.5 Content Safety compared

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

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Nemotron 3.5 Content SafetynvidiaThis modelNvidia Nemotron 3.5 Super VLnvidiaRemove
Providernvidianvidia
Discovery tierOpen weightsOpen weights
AddedSep 19, 2026Oct 15, 2026
Limits
Context window131.07K262.14KBest
Max output32.77KBest16.38K
Average output16 tokens1.1K tokens
Pricing, USD per 1M tokens
Input$0.05Best$0.15
Output$0.15Best$0.50
Cache read$0.025$0.02Best
Performance
Throughput—654.7 tok/s
Time to first token—1.8 s
Request success (24h)—98.0%
Benchmark indexes
Intelligence Index—26.5
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.

  • Nemotron 3.5 Content Safety
  • Nvidia Nemotron 3.5 Super VL

Intelligence Index

  • Nemotron 3.5 Content Safety—
  • Nvidia Nemotron 3.5 Super VL26.5
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 14.8%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 2.0%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 999 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 1,162 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 8.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 69.0%

  • MLCR-AA

    Long-context reasoning over medical records

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 13.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 30.7%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 0.0%

  • SciCode

    Scientific computing in Python

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 47.8%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Nemotron 3.5 Content Safety: —
    • Nvidia Nemotron 3.5 Super VL: 69.0%

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

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-3.5-content-safety",
    "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-3.5-content-safety",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

nvidia

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