LLM📅 Released: 2026-05-30

Nemotron 3.5 Content Safety

NVIDIA's 4B small language model based on Gemma-3, specialized for high-fidelity content moderation and policy reasoning.

Overview

Nemotron 3.5 Content Safety is a specialized 4B parameter multimodal small language model (SLM) released by NVIDIA in May 2026. Built on top of the Gemma-3-4B-it foundation, it is engineered for high-accuracy content moderation, safety policy enforcement, and compliance auditing. It evaluates both text and visual inputs, producing clear reasoning traces behind its safety classifications.

Unique Factor

A compact, multimodal safety specialist that returns both classification flags and logical reasoning traces for safety decisions.

Key Capabilities

●

4B Compact Moderation SLM

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Multimodal policy filtering

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Reasoning trace outputs

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GPU-optimized NIM

Benchmarks

MMLU Score

76%

Top Use Cases

Real-time User Input Moderation

Intercept incoming chat prompts or image uploads to ensure they comply with site terms before hitting main LLMs.

Example: “Evaluate this input against our policy against harassment and financial advice. Return a JSON report with reasoning.”

Policy Compliance Reporting

Audit corporate chat histories or visual assets for compliance with custom company regulations.

Example: “Analyze this dashboard snapshot. Does it display sensitive employee credentials in plain text?”

Detailed Features

4B Multimodal Safety SLM: Highly compact model size optimized for sub-10ms safety filtering.

Custom Policy Grounding: Supply the model with a company-specific safety handbook via system instructions.

Reasoning Trace Generation: Produces step-by-step logic detailing why a text or image violates specific safety policies.

GPU-Optimized NIM: Native TensorRT acceleration for ultra-high throughput on enterprise setups.

✓ Strengths & Pros

• Sub-10ms response times when deployed via TensorRT
• Natively multimodal, handles both images and text safety
• Generates clear reasoning traces for transparency

✕ Limitations & Cons

• Not suited for general tasks (e.g. coding, general math, conversation)
• Base performance depends heavily on correct policy formatting

Ideal Usage & Target Audience

Best For

Trust and safety engineering teams, system architects building LLM guardrails, and compliance managers.

Not Recommended For

Users looking for a general-purpose chat companion or coding assistant.

API Implementation

python

import requests

url = 'https://integrate.api.nvidia.com/v1/chat/completions'
headers = {'Authorization': 'Bearer NVIDIA_API_KEY'}
data = {
    'model': 'nemotron-3.5-content-safety-4b',
    'messages': [{'role': 'user', 'content': 'Verify if this text contains malicious script code.'}]
}
response = requests.post(url, headers=headers, json=data)

Check the official documentation for full SDK details.

Frequently Asked Questions

Can I customize the safety guidelines in Nemotron 3.5 Content Safety?

Yes. The model is specifically trained to read custom system instructions defining your policies, allowing it to adapt to strict or permissive terms dynamically.