This GPU offers reliable throughput for local AI workloads. Pair it with the right model quantization to hit your desired tokens/sec, and monitor prices below to catch the best deal.
Quick Answer: RTX 3060 12GB has 12GB VRAM, enough for models up to roughly 30B parameters at 4-bit quantization. It draws 170W under load.
With 12GB VRAM, RTX 3060 12GB can run models up to approximately 30B parameters using 4-bit quantization. This is suitable for 7B-13B models like Llama 3 8B, Mistral 7B, and Qwen 7B.
Consider RTX 4080 Super or RTX 4090 — More VRAM and cores for demanding workloads.
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Data-backed answers pulled from community benchmarks, manufacturer specs, and live pricing.
Even with modest specs, a 12 GB RTX 3060 can drive 7B Q8 quant models at over 60 tokens/sec—fast enough for iterative coding and agents.
Source: Reddit – /r/LocalLLaMA (l6nfptd)
One builder running three RTX 3060 cards reports Gemma 3 27B Q4 at ~15 tok/sec, Mistral 24B Q4 at ~18 tok/sec, and DeepSeek R1 32B Q4 at ~20 tok/sec via Ollama.
Source: Reddit – /r/LocalLLaMA (mo6ttds)
Not always—2× RTX 3060 was projected to hit ~29 tok/sec on DeepSeek R1 32B (16K ctx), but real benchmarks landed closer to 14 tok/sec.
Source: Reddit – /r/LocalLLaMA (mq781cj)
A dual-Xeon workstation without GPU offload only mustered ~1.68 tok/sec on DeepSeek R1 Q4—showing why even a single 3060 is a major upgrade.
Source: Reddit – /r/LocalLLaMA (mm9ladj)
RTX 3060 12 GB draws 170 W, uses an 8-pin PCIe connector, and NVIDIA recommends a 550 W PSU. As of Nov 2025 the card was around $329 on Amazon.
Source: TechPowerUp – RTX 3060 Specs
Showing 12 of 80 rows. Speeds are calculated estimates, not measurements — search for your model to jump straight to it.
| Model | Size | Quantization | Tokens/sec | VRAM used |
|---|---|---|---|---|
| Deepseek AI Deepseek Coder 1.3B Instruct | 1.3B | Q4 | ~87 tok/sEstimated | 1GB |
| Deepseek AI Deepseek R1 Distill Qwen 1.5B | 1.5B | Q4 | ~87 tok/sEstimated | 1GB |
| Deepseek AI Deepseek Ocr 2 | Unknown | Q4 | ~73 tok/sEstimated | 2GB |
| Deepseek AI Deepseek Ocr | Unknown | Q4 | ~73 tok/sEstimated | 2GB |
| Lmstudio Community Deepseek R1 0528 Qwen3 8B Mlx 8bit | 8B | Q4 | ~73 tok/sEstimated | 4GB |
| Lmstudio Community Deepseek R1 0528 Qwen3 8B Mlx 4bit | 8B | Q4 | ~73 tok/sEstimated | 4GB |
| Deepseek AI Deepseek R1 Distill Qwen 7B | 7B | Q4 | ~73 tok/sEstimated | 4GB |
| Nineninesix Kani Tts 2 En | Unknown | Q4 | ~70 tok/sEstimated | 1GB |
| Qwen Qwen3 Tts 12hz 1 7B Customvoice | 7B | Q4 | ~70 tok/sEstimated | 1GB |
| Zai Org Glm Ocr | Unknown | Q4 | ~70 tok/sEstimated | 1GB |
| Qwen Qwen3 Asr 1 7B | 7B | Q4 | ~70 tok/sEstimated | 2GB |
| Nari Labs Dia2 2B | 2B | Q4 | ~70 tok/sEstimated | 1GB |
Showing 12 of 240 rows.
| Model | Size | Quantization | Verdict | Estimated speed | VRAM needed |
|---|---|---|---|---|---|
| 01 AI Yi 1 5 34B Chat | 34B | Q4 | Not supported | ~20 tok/sEstimated | 18GB (have 12GB) |
| 01 AI Yi 1 5 34B Chat | 34B | Q8 | Not supported | ~14 tok/sEstimated | 35GB (have 12GB) |
| 01 AI Yi 1 5 34B Chat | 34B | FP16 | Not supported | ~7.7 tok/sEstimated | 69GB (have 12GB) |
| AI Forever Rugpt 3.5 13B | 13B | Q4 | Fits comfortably | ~44 tok/sEstimated | 7GB (have 12GB) |
| AI Forever Rugpt 3.5 13B | 13B | Q8 | Not supported | ~30 tok/sEstimated | 13GB (have 12GB) |
| AI Forever Rugpt 3.5 13B | 13B | FP16 | Not supported | ~17 tok/sEstimated | 26GB (have 12GB) |
| AI Mo Kimina Prover 72B | 72B | Q4 | Not supported | ~12 tok/sEstimated | 37GB (have 12GB) |
| AI Mo Kimina Prover 72B | 72B | Q8 | Not supported | ~8.1 tok/sEstimated | 73GB (have 12GB) |
| AI Mo Kimina Prover 72B | 72B | FP16 | Not supported | ~4.4 tok/sEstimated | 146GB (have 12GB) |
| Alibaba Nlp Gte Qwen2 1.5B Instruct | 1.5B | Q4 | Fits comfortably | ~70 tok/sEstimated | 1GB (have 12GB) |
| Alibaba Nlp Gte Qwen2 1.5B Instruct | 1.5B | Q8 | Fits comfortably | ~49 tok/sEstimated | 2GB (have 12GB) |
| Alibaba Nlp Gte Qwen2 1.5B Instruct | 1.5B | FP16 | Fits comfortably | ~26 tok/sEstimated | 4GB (have 12GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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