Nemotron-3.5-Content-Safety
The Nemotron 3.5 Content Safety model is a small language model (SLM) that uses Google's Gemma-3-4B-it as the base and is fine-tuned by NVIDIA on multimodal, multilingual, and reasoning-oriented content-safety datasets. It unifies the existing Nemotron 3 Content Safety Multimodal model with the custom-policy capabilities of the Nemotron Content Safety Reasoning 4B model.
Params
4.3 B
Context
—
Downloads 30d
35 K
Likes
66
Download history
tracking started — chart appears after 7 days of snapshots (6 recorded)35 K downloads in the last 30 days
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | bf16 | 8.6 GB | 10.6 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Run it
copy-paste, exact tags checked against the Hub$ curl -s https://aimodelscomparison.com/api/v1/models/nemotron-3-5-content-safety
{
"hf_id": "nvidia/Nemotron-3.5-Content-Safety",
"params_b": 4.30,
"context_length": null,
"license": { "id": "other", "commercial": "unknown" },
"downloads_30d": 34521,
"vram_estimates": [
{ "quant": "bf16", "gb": 10.6 }
],
"updated_at": "2026-10-19T06:02:49Z"
}
Use via API
via OpenRouter · USD per 1M tokens · synced 2026-10-24$0.20
input / 1M
$0.20
output / 1M
—
cached input / 1M
$0.40
1M in + 1M out
:free variant
Free in · Free out
- Context window
- 131,072 tokens
- Max output
- 117,964 tokens
- Providers
- 1
- Cheapest provider
- DeepInfra · $0.20 / $0.20
- Best throughput
- —
- AA Intelligence / Coding / Agentic
- — / — / —
✗ Tool calling
✓ Reasoning
✗ Structured outputs
✓ Image input
✗ File input
✗ Audio input
✗ Prompt caching
Specifications
- Architecture
- Gemma3ForConditionalGeneration
- Parameters
- 4.3 B
- Tensor type
- BF16
- Licence
- other
- First seen on the Hub
- 2026-05-22
- Training datasets
- nvidia/Nemotron-3.5-Content-Safety-Dataset
- Added to our catalog
- 2026-10-20
Compare with any text-generation model