NVIDIA GeForce RTX 5060 Ti 8GB — Local LLM Performance & Compatibility

作者: Jakub Rusinowski · 最后更新: 2026年7月12日

Same GB206 chip and 448 GB/s bandwidth as the 16GB variant, but 8 GB VRAM limits it to 7–8B models in Q4. The cheaper of the two RTX 5060 Ti configurations.

Technical Specifications

VRAM8 GB
Memory Bandwidth448 GB/s
TDP180 W
ArchitectureBlackwell GB206
Release Year2025
MSRP at Launch$379
Inference Speed (Llama 3.1 8B Q4_K_M)40–83 tok/s (estimated)
Inference Speed (Llama 3.3 70B Q4_K_M)Does not fit — needs ~44 GB of 8 GB usable
Buy This HardwareNVIDIA GeForce RTX 5060 Ti 8GB — 8 GB VRAM · 180 W board powerDeploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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NVIDIA GeForce RTX 5060 Ti 8GB
8 GB VRAM · 180 W board power
2026年价格波动较大——请以当前商品页价格为准。
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LLMs Compatible with 8 GB VRAM

All models below run comfortably in 8 GB VRAM with Q4_K_M quantization.

Llama 3.1 FamilyLlama 3.1 8B Instruct · 6 GB VRAM · Q4_K_M · ollama run llama3.1
Llama 3.2 FamilyLlama 3.2 11B Vision Instruct · 7 GB VRAM · Q4_K_M · llama-3-2
Qwen 2.5 FamilyQwen 2.5 7B Instruct · 5 GB VRAM · Q4_K_M · ollama run qwen2.5:7b
Gemma 3Gemma 3 4B Instruct · 3 GB VRAM · Q4_K_M · ollama run gemma3:4b
Phi-4 MiniPhi-4 Mini (3.8B) · 3 GB VRAM · Q4_K_M · ollama run phi4-mini
SmolLM2SmolLM2 1.7B Instruct · 2 GB VRAM · Q4_K_M · ollama run smollm2:1.7b
Ministral 3Ministral 3 8B · 6 GB VRAM · Q4_K_M · ollama run ministral-3:8b
IBM Granite 4.2Granite 4.2 8B · 6 GB VRAM · Q4_K_M · ollama run granite4.2:8b

Best Use Cases

Quick Start with Ollama

Install Ollama then run the recommended model for this GPU:

ollama run llama3.1:8b

FAQ

Can the NVIDIA GeForce RTX 5060 Ti 8GB run local LLMs?

Yes — the NVIDIA GeForce RTX 5060 Ti 8GB has 8 GB VRAM and runs Same GB206 chip and 448 GB/s bandwidth as the 16GB variant, but 8 GB VRAM limits it to 7–8B models in Q4. The cheaper of

How fast is the NVIDIA GeForce RTX 5060 Ti 8GB for AI inference?

The NVIDIA GeForce RTX 5060 Ti 8GB is estimated to run Llama 3.1 8B at 40–83 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 8 GB usable. These are modelled estimates, not measurements — see /en/methodology.

What LLMs can I run on 8 GB VRAM?

With 8 GB you can run: Llama 3.1 Family, Llama 3.2 Family, Qwen 2.5 Family, Gemma 3, Phi-4 Mini. Use Ollama for the easiest setup: ollama run llama3.1:8b.

Can I Run It? — NVIDIA GeForce RTX 5060 Ti 8GB

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