NVIDIA RTX 3060 12GB - 12GB usable
An easy, efficient entry point for local AI when a fair used example is available.
Specifications
| Brand | NVIDIA |
|---|---|
| Model | RTX 3060 12GB |
| Usable VRAM | 12GB |
| Architecture | Ampere |
| CUDA / Stream Processors | 3,584 |
| Memory Bandwidth | 360 GB/s |
| TDP | 170W |
| FP32 TFLOPS | 13 |
Current Offers
No fresh used offer today · recently $268 on eBayNew from $380
Prices last updated:
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Price History
- eBayno current offer
- Amazon$380current
- Newegg$474near high
For AI / LLM Use
Entry-level for local AI. Handles 7B-8B models well. Slower generation, usable but not snappy.
What Models Can It Run?
- 14B Q4_K_M, 7B full precision
- 7B Q6_K, 14B Q3_K (tight)
- 7B Q4_K_M only
Estimated Performance
Generation: ~27 tokens/sec
Prefill: ~232 tokens/sec
Recommended Quantisations
- Q4_K_M for 14B (tight fit)
- Q6_K or Q8 for 7B models
Pros & Cons
Pros
- Ampere architecture: broad CUDA software support
- Consumer card: easy to install, display output
- 12GB in a normal desktop card with display outputs
- Low setup friction and broad software support
Cons
- 12GB usable VRAM: may need quantization for 30B+ models
- Moderate memory bandwidth: not the fastest for inference
- 12GB limits larger models and long-context workloads
- Some used listings command an AI-driven VRAM premium
Community Verdict
- r/LocalLLaMA
Best entry point for local AI. 12GB handles 7B-8B models comfortably at a fraction of 3090 prices.
Source