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NVIDIA GeForce RTX 5060 8GB
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Compatibility Report

Gemma 2 9B Instruct on NVIDIA GeForce RTX 5060 8GB

Yes — RTX 5060 8GB handles Gemma 2 9B Instruct well at Q4_K_M — 32 tok/s. Solid daily-driver performance on 8 GB VRAM.

Model Size

9.24B

Device VRAM

8 GB

Bandwidth

448 GB/s

Quantization

Q4_K_M

Benchmarks

Performance by Quantization

OwnRig currently has one published compatibility entry for Gemma 2 9B Instruct on NVIDIA GeForce RTX 5060 8GB at Q4_K_M. This is the best supported pairing we can stand behind today.

QuantizationSpeedTTFTFits in VRAMRatingConfidence
Q4_K_M32 tok/s240ms✓ YesGoodestimated

Notes

Q4_K_M

Q4_K_M 5.6GB fits with ~2.4GB headroom. 9.24B model, 8GB is tight. Estimated for rtx-5060-8gb; verify with community benchmarks.

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 5060 8GB

NVIDIA GeForce RTX 5060 8GB has 8 GB at 448 GB/s. Street price: $299.

See all models NVIDIA GeForce RTX 5060 8GB can run →

Estimate method: Estimated from rtx-4060-8gb matrix rows scaled for rtx-5060-8gb memory bandwidth (Ada Gate A methodology). Reference hardware source: nvidia.com (2026-05-26)

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.

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Trademark Notice: NVIDIA, GeForce, and RTX are trademarks of NVIDIA Corporation. AMD and Radeon are trademarks of Advanced Micro Devices, Inc. Apple, Mac, and Apple Silicon are trademarks of Apple Inc. All other product names, logos, and brands are property of their respective owners. AI model names (Llama, Gemma, Mistral, Qwen, etc.) are trademarks of their respective creators. Use of these names and logos is for identification purposes only and does not imply endorsement.

Independence & Affiliates: OwnRig is an independent resource. We are not affiliated with, endorsed by, or sponsored by any hardware manufacturer, AI model provider, or retailer. Our recommendations are based on technical merit and community benchmarks. Some links on this site are affiliate links. If you purchase through them, we may earn a small commission at no extra cost to you. This does not influence our recommendations.

Data Accuracy: Performance figures are estimates based on community benchmarks and may vary by configuration, driver version, and software. Prices are approximate US retail as of March 2026 and may vary by retailer and region. VRAM requirements are calculated from model parameters with overhead estimates. Always verify specifications with manufacturer documentation before purchasing.

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