Table of Contents
Gemma 2 ships in 2B, 9B, and 27B sizes. The 5060 Ti hosts the first two well; 27B requires aggressive quantisation.
TL;DR
For most workloads on a 5060 Ti, host Gemma 2 9B at FP8. For very fast / low-VRAM use, Gemma 2 2B FP16. Gemma 2 27B INT4 just barely fits but is tight; consider 5090 instead.
Gemma 2 variants on the 5060 Ti
| Variant | FP16 | FP8 | AWQ-INT4 | Recommended |
|---|---|---|---|---|
| Gemma 2 2B | 4 GB | 2 GB | 1 GB | FP16 |
| Gemma 2 9B | 18 GB ❌ | 9 GB ✅ | 6 GB ✅ | FP8 |
| Gemma 2 27B | 54 GB ❌ | 27 GB ❌ | 14 GB ⚠️ | INT4 (tight) |
Which Gemma should you pick?
- Light chatbot or embedded tool: Gemma 2 2B FP16
- Production chatbot, safety-tuned: Gemma 2 9B FP8
- Higher quality reasoning: 9B FP8 still — 27B INT4 isn't enough quality lift to justify hardware
- Need 27B quality: upgrade to 5090 or 6000 Pro
Verdict
Gemma 2 9B FP8 on a 5060 Ti is the production deployment most teams should run. 2B for ultra-low-latency, 27B requires bigger hardware.
Bottom line
Gemma 2 9B FP8 — safety-tuned, decent reasoning, fits 16 GB. The right Gemma deployment for the 5060 Ti tier.
