GoogleGemma 2 27B Instruct on NVIDIA GeForce RTX 4060 8GB
RTX 4060 8GB cannot run Gemma 2 27B Instruct. 8 GB VRAM is insufficient at any quantization level.
Model Size
27.23B
Device VRAM
8 GB
Bandwidth
272 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 2 27B Instruct on NVIDIA GeForce RTX 4060 8GB at Q3_K_M. This pairing has limitations — check the rating and notes below.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | – | – | ✗ Offload | Not viable | estimated |
Notes
Q3_K_M
27B model. Minimum Q3_K_M needs 13.3GB.
About Gemma 2 27B Instruct
Gemma 2 27B Instruct (27.23B) is a chat, coding, reasoning, multi-purpose model. Google's 27B model with effective knowledge distillation. Reasoning and coding at a size that fits on a single 24 GB GPU at Q4. Limited to 8K context.
View all Gemma 2 27B Instruct hardware options →About NVIDIA GeForce RTX 4060 8GB
NVIDIA GeForce RTX 4060 8GB has 8 GB at 272 GB/s. Street price: $289.
See all models NVIDIA GeForce RTX 4060 8GB can run →Estimate method: Q3_K_M 13.3GB exceeds 8GB. 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.