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NVIDIA RTX 3060 (12GB)

The NVIDIA RTX 3060 (12GB) features 12 GB of dedicated VRAM and 360 GB/s memory bandwidth, supporting CUDA and TensorRT-LLM runtimes for full-precision and quantized inference.

Memory

12 GB

Usable Memory Ceiling

12 GB

Bandwidth

360 GB/s

Max Inference Class

14B Models (Q4)

TDP

170W

VRAM Scaling by Context Length

Estimated memory requirements as context length increases. Curves crossing above the reference line indicate Out of Memory (OOM).

Gemma 3 270M (0.27B)Ministral 3 3B (3B)MiMo V2.6 Distill Qwen 9B (9B)K2 Horizon MoVA 36B A4B (36B (4B active))

Precision:

Best Models to Run on NVIDIA RTX 3060 (12GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA RTX 3060 (12GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#112

Phi-4 Reasoning Plus

14B

INT4

22 tok/s

~3.6s

#125

Qwen3.5-9B

9B

INT4
Q8

50 tok/s

29 tok/s

~2.0s

~2.1s

#128

K2 Horizon 7B

7B

INT4
Q8

62 tok/s

38 tok/s

~1.5s

~1.5s

#135

Gemma 4 12B

11.95B

INT4

27 tok/s

~2.8s

#140

Qwen3.5-4B

4B

INT4
Q8
FP16

95 tok/s

61 tok/s

34 tok/s

~900 ms

~906 ms

~919 ms

#144

GLM-4V

9B

INT4

36 tok/s

~2.0s

#150

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

16 tok/s

9 tok/s

5 tok/s

~6.2s

~6.2s

~6.8s

#158

Granite 4.2 8B

8B

INT4
Q8

56 tok/s

32 tok/s

~1.7s

~1.9s

#159

Gemma 4 E4B

8B

INT4
Q8

56 tok/s

32 tok/s

~1.7s

~1.9s

#166

Phi-4

14B

INT4

34 tok/s

~3.0s

#178

OLMo 3 7B Think

7B

INT4
Q8

44 tok/s

29 tok/s

~1.5s

~1.7s

#179

DeepSeek-R1 14B

14B

INT4

35 tok/s

~3.0s

#183

Ministral 3 14B

14B

INT4

22 tok/s

~3.6s

#186

Gemma 3 12B

12B

INT4

39 tok/s

~2.6s

#189

Ministral 3 8B

8B

INT4
Q8

40 tok/s

25 tok/s

~1.7s

~2.1s

#191

MiniCPM5-2B

2B

INT4
Q8
FP16

146 tok/s

102 tok/s

61 tok/s

~480 ms

~483 ms

~489 ms

#192

Qwen3.5-2B

2B

INT4
Q8
FP16

146 tok/s

102 tok/s

61 tok/s

~480 ms

~483 ms

~489 ms

#194

Qwen2.5-14B

14B

INT4

34 tok/s

~3.0s

#200

Gemma 4 E2B

5.1B

INT4
Q8
FP16

80 tok/s

50 tok/s

24 tok/s

~1.1s

~1.1s

~1.4s

#202

DeepSeek-R1 8B

8B

INT4
Q8

57 tok/s

34 tok/s

~1.7s

~1.8s

Inference Capacity

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

14B Models

8-bit

Q8

8B Models

16-bit

FP16

3B Models

Fine-Tuning Capacity

Hardware capacity for local training and adapter fine-tuning.

Context Length:

QLoRA

4-bit

14B Models

LoRA

16-bit

8B Models

Full Parameter Training

1B Models

Workload Recommendations

Guidance for optimal precision and operational ceilings on NVIDIA RTX 3060 (12GB).

Inference Sweet Spot

Optimal for 8B models across extended context (32k+). 14B models fit comfortably at Q4 precision with standard context.

Bandwidth & Speed Profile

With 360 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 80 tok/s on an 8B Q4 model and 9 tok/s on a 70B Q4 model.

Frequently Asked Questions