GoogleGemma 3 27B on NVIDIA GeForce RTX 4060 Ti 16GB
RTX 4060 Ti 16GB runs Gemma 3 27B at Q3_K_M — 6 tok/s due to limited memory bandwidth. Slow but functional — see all options below.
Model Size
27.23B
Device VRAM
16 GB
Bandwidth
288 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 3 27B on NVIDIA GeForce RTX 4060 Ti 16GB at Q3_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | 6 tok/s | 1200ms | ✓ Yes | Marginal | estimated |
Notes
Q3_K_M
Barely fits at Q3_K_M (13.3GB). Low bandwidth (288 GB/s) severely limits throughput. Usable but slow.
About Gemma 3 27B
Gemma 3 27B (27.23B) is a chat, coding, reasoning, multi-purpose model. Google's largest open-weight model before Gemma 4. Capable reasoning and instruction following. At 27B parameters, it sits between 8B models (too limited) and 70B models (too expensive). Wide multilingual support. Fits on 24 GB GPUs at Q4.
View all Gemma 3 27B hardware options →About NVIDIA GeForce RTX 4060 Ti 16GB
NVIDIA GeForce RTX 4060 Ti 16GB has 16 GB at 288 GB/s. Street price: $449.
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Estimate method: Performance estimates based on model size and device bandwidth. Reference hardware source: github.com (2026-03-15)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.