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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

Side by side

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 modelDeepSeek V4 Flash 0731 (Thinking)DeepSeekRemove
ProvidernvidiaDeepSeek
Discovery tierOpen weightsOpen weights
AddedSep 19, 2026Aug 1, 2026
Limits
Context window131.07K1.05MBest
Max output32.77K131.07KBest
Average output16 tokens755 tokens
Pricing, USD per 1M tokens
Input$0.05$0.05
Output$0.15Best$0.16
Cache read$0.025$0.013Best
Performance
Throughput—147.4 tok/s
Time to first token—5.7 s
Request success (24h)—99.8%
Benchmark indexes
Intelligence Index—34.3
Coding Index—69.1
Capabilities
ReasoningYesYes
ToolsNoYes
Structured outputNoYes
Reasoning effort—none, low, high, max

Public evaluations

Benchmarks

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

  • Nemotron 3.5 Content Safety
  • DeepSeek V4 Flash 0731 (Thinking)

Intelligence Index

  • Nemotron 3.5 Content Safety—
  • DeepSeek V4 Flash 0731 (Thinking)34.3
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 69.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 54.0%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 23.0%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 1,257 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 1,433 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 11.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 79.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 38.6%

  • GPQA Diamond

    Graduate-level science questions

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 90.8%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 12.1%

  • SciCode

    Scientific computing in Python

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 50.3%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Nemotron 3.5 Content Safety: —
    • DeepSeek V4 Flash 0731 (Thinking): 79.7%

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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