NVIDIA GeForce RTX 5060 — Local LLM Performance & Compatibility

Entry-level Blackwell GPU at $299. 8 GB VRAM is enough for any 7–8B model in Q4. 145W TDP makes it efficient for always-on AI use.

Technical Specifications

VRAM8 GB
Memory Bandwidth448 GB/s
TDP145 W
ArchitectureBlackwell GB206
Release Year2025
MSRP at Launch$299
Inference Speed (Llama 3.1 8B Q4_K_M)~68 tokens/sec

LLMs Compatible with 8 GB VRAM

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

Llama 3.2 Family8 GB VRAM · Q4_K_M · ollama run llama3.2-vision:11b
Llama 3.1 Family6 GB VRAM · Q4_K_M · ollama run llama3.1
Qwen 2.5 Family5 GB VRAM · Q4_K_M · ollama run qwen2.5:7b
Gemma 2 Family8 GB VRAM · Q4_K_M · ollama run gemma2
Phi-4 Mini2 GB VRAM · Q4_K_M · ollama run phi4-mini
Mistral Familymistral
SmolLM21 GB VRAM · Q4_K_M · ollama run smollm2:1.7b
DeepSeek R16 GB VRAM · Q4_K_M · ollama run deepseek-r1:8b

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 run local LLMs?

Yes — the NVIDIA GeForce RTX 5060 has 8 GB VRAM and runs Entry-level Blackwell GPU at $299. 8 GB VRAM is enough for any 7–8B model in Q4. 145W TDP makes it efficient for always-

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

The NVIDIA GeForce RTX 5060 runs Llama 3.1 8B at ~68 tokens/sec with Q4_K_M quantization.

What LLMs can I run on 8 GB VRAM?

With 8 GB you can run: Llama 3.2 Family, Llama 3.1 Family, Qwen 2.5 Family, Gemma 2 Family, Phi-4 Mini. Use Ollama for the easiest setup: ollama run llama3.1:8b.

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