GoogleGemma 2 9B Instruct on NVIDIA GeForce RTX 4060 8GB
Yes — RTX 4060 8GB handles Gemma 2 9B Instruct well at Q4_K_M — 28 tok/s. Solid daily-driver performance on 8 GB VRAM.
Model Size
9.24B
Device VRAM
8 GB
Bandwidth
272 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 2 9B Instruct on NVIDIA GeForce RTX 4060 8GB at Q4_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q4_K_M | 28 tok/s | 240ms | ✓ Yes | Good | estimated |
Notes
Q4_K_M
Q4_K_M 5.6GB fits with ~2.4GB headroom. 9.24B model, 8GB is tight.
About Gemma 2 9B Instruct
Gemma 2 9B Instruct (9.24B) is a chat, coding, reasoning, multi-purpose model. Google's 9B model with effective knowledge distillation. Competitive with Llama 3.1 8B on most benchmarks. Shorter max context (8K) is the main limitation vs Llama.
View all Gemma 2 9B 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: 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.