Content moderation needs high throughput, low latency, and tight data privacy. The RTX 5060 Ti 16GB at our hosting fits all three.
Contents
Moderation Models (fit 16 GB)
| Model | Params | VRAM | Use |
|---|---|---|---|
| Llama Guard 3 8B | 8B | 8 GB (FP8) | Harm categories |
| ShieldGemma 9B | 9B | 9.5 GB (FP8) | Safety classification |
| Phi-3 mini + custom prompt | 3.8B | 3.8 GB | Fast custom moderation |
| BERT / DeBERTa custom | 350M | 1.4 GB | Topic / sentiment classifiers |
Throughput
| Model | Messages/sec | Daily capacity |
|---|---|---|
| Llama Guard 3 8B FP8 | ~60 (200-token msgs, batch 16) | ~5.2M/day |
| Phi-3 mini FP8 | ~150 | ~13M/day |
| DeBERTa-v3-large classifier | ~800 | ~69M/day |
For volume moderation use DeBERTa classifiers; reserve LLM-style moderation (Llama Guard) for edge cases.
Pipelines
- Fast classifier first: DeBERTa labels obvious cases
- LLM second opinion on ambiguous: Llama Guard 3 rules on items scoring near threshold
- Human review queue: final layer for edge cases
Multimodal Content
For image moderation pair with Qwen2.5-VL 7B (~8 GB FP8) or a vision classifier. For audio, run Whisper transcribe first then text moderation.
- Image moderation with Qwen-VL: ~1-2 s per image
- Audio: 1 hour audio in ~65 s (Whisper Turbo) + near-instant text moderation
For a medium social platform (millions of posts/day) one 5060 Ti handles the moderation LLM layer with room to spare.
Content Moderation on Blackwell 16GB
Llama Guard + classifiers, millions of messages/day. UK dedicated hosting.
Order the RTX 5060 Ti 16GBSee also: classification, Phi-3 guide, Qwen-VL, multimodal.
