RTX 3060 Ti
51 AI models fit in 8 GB VRAM at Q4 native. 17 more run with CPU offloading. Real benchmarks below.
llama.cpp 0.2.x · CUDA 12 · Ubuntu 22.04 · Prices verified on Amazon · methodology →
Execution Context
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Full Specifications
NVIDIA · 2020-12
| VRAM | 8 GB GDDR6 |
| Bandwidth | 448 GB/s |
| FP16 TFLOPS | 16.2 |
| AI Score | 38 / 140 |
| CUDA Cores | 4,864 |
| Tensor Cores | 152 |
| TDP | 200 W |
| PCIe | Gen 4 |
| Slots | 2 |
| Power Connector | 2x 8-pin |
| Price Band | Preis-Leistung |
| Released | 2020-12 |
AI Benchmarks
Real inference measurements — llama.cpp Q4_K_M
| Task | Result |
|---|---|
| Llama 1B Q4 | 236 tok/s |
| Llama 3B Q4 | 94 tok/s |
| Llama 7B Q4 | 32 tok/s |
| Llama 13B Q4 | VRAM N/A |
| Llama 30B Q4 | VRAM N/A |
| Llama 70B Q4 | Offload or multi-GPU |
| Stable Diffusion 512px | 5.5s / img |
| Whisper Large RTF | 0.65x |
RTF < 1.0 = faster than real time. For Stable Diffusion and Whisper lower is better; for tokens/s higher is better.
Compare RTX 3060 Ti with another GPU
Is an upgrade worth it? Compare specs and real benchmarks side by side.
Open comparator →Compatible AI Models — RTX 3060 Ti
51 models run fully in VRAM · 17 with CPU offloading
Whisper Large V3
Stable Diffusion 3.5 Medium
Stable Diffusion 3 Medium
Gemma 4 12B
Stable Diffusion XL
Qwen2.5 Coder 14B
Qwen3 14B
Gemma 3 12B
Show all 51 compatible models →
Also runs with CPU offloading (17)
- Flux.1 Dev 8 GB Q2
- Stable Diffusion 3.5 Large 8 GB Q2
- Gemma 4 27B 7.4 GB Q2 How to install →
- Gemma 2 27B 8 GB Q2 How to install →
- Mistral Small 3 7.2 GB Q2 How to install →
- Phi-4 4.2 GB Q2 How to install →
- Flux.1 Schnell 8 GB Q2
- Devstral Small 2 24B 6.6 GB Q2 How to install →
- DeepSeek R1 Distill 14B 4.2 GB Q2 How to install →
- Qwen3.5 27B 7.4 GB Q2 How to install →
- Magistral Small 24B 6.6 GB Q2 How to install →
- Qwen2.5 14B 4.2 GB Q2 How to install →
- DeepSeek Coder V2 5 GB Q2 How to install →
- Mistral Small 3.2 6.6 GB Q2 How to install →
- StarCoder 2 15B 4.5 GB Q2 How to install →
- Mistral Small 3.1 6.6 GB Q2 How to install →
- DeepSeek V2 Lite 5 GB Q2 How to install →
RTX 3060 Ti · Amazon
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RTX 3060 Ti for Local AI
La RTX 3060 Ti con 8GB de GDDR6 es perfecta para empezar con IA local. Cubre todos los modelos 7B populares en Q4 (Llama 3.1 8B, Mistral 7B, Qwen2.5 7B, DeepSeek R1 Distill 8B) con velocidades decentes. Para casos de uso ligeros como chat, coding assistance y transcripción de audio, esta GPU tiene todo lo necesario.
En benchmarks reales, la RTX 3060 Ti genera 32 tokens/segundo con Llama 7B Q4 — suficiente para conversación en tiempo real. Whisper para transcripción de voz funciona perfectamente. Para generación de imágenes, Stable Diffusion 3 Medium y SD 3.5 Medium son compatibles.
Si buscas tu primera GPU para IA local con un presupuesto ajustado, la RTX 3060 Ti es un punto de entrada sólido. Consulta nuestra guía para empezar con IA local y usa la calculadora de VRAM para verificar la compatibilidad con tu modelo favorito.
Plan your full AI build
RTX 3060 Ti · 8 GB VRAM — configure PSU, RAM, storage and check compatible models.
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