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NVIDIA RTX 4060 (8GB)

The NVIDIA RTX 4060 (8GB) features 8 GB of dedicated VRAM and 272 GB/s memory bandwidth, supporting CUDA and TensorRT-LLM runtimes for full-precision and quantized inference.

Memory

8 GB

Usable Memory Ceiling

8 GB

Bandwidth

272 GB/s

Max Inference Class

8B Models (Q4)

TDP

115W

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)NVIDIA Nemotron 3 Nano 30B-A3B (3.5B (30B active))Granite 4.2 8B (8B)ERNIE-4.5-21B-A3B-Base (21B (3B active))

Precision:

Best Models to Run on NVIDIA RTX 4060 (8GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA RTX 4060 (8GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#113

Qwen3.5-9B

9B

INT4

39 tok/s

~1.7s

#118

K2 Horizon 7B

7B

INT4

49 tok/s

~1.3s

#128

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8

12 tok/s

7 tok/s

~5.3s

~5.8s

#132

Qwen3.5-4B

4B

INT4
Q8

77 tok/s

48 tok/s

~768 ms

~776 ms

#146

Granite 4.2 8B

8B

INT4

44 tok/s

~1.5s

#150

Gemma 4 E4B

8B

INT4

44 tok/s

~1.5s

#169

OLMo 3 7B Think

7B

INT4

32 tok/s

~1.4s

#177

Gemma 3 12B

12B

INT4

27 tok/s

~2.6s

#182

Ministral 3 8B

8B

INT4

28 tok/s

~1.8s

#183

Qwen3.5-2B

2B

INT4
Q8
FP16

122 tok/s

83 tok/s

48 tok/s

~410 ms

~414 ms

~423 ms

#184

MiniCPM5-2B

2B

INT4
Q8
FP16

122 tok/s

83 tok/s

48 tok/s

~410 ms

~414 ms

~423 ms

#188

Gemma 4 E2B

5.1B

INT4
Q8

63 tok/s

37 tok/s

~965 ms

~1.1s

#189

Qwen3-4B

4B

INT4
Q8

77 tok/s

48 tok/s

~768 ms

~776 ms

#190

DeepSeek-R1 8B

8B

INT4

45 tok/s

~1.5s

#193

Ministral 3 3B

3B

INT4
Q8

60 tok/s

45 tok/s

~594 ms

~600 ms

#197

Gemma 2 9B

9B

INT4

39 tok/s

~1.7s

#198

Qwen2.5-7B

7B

INT4

49 tok/s

~1.3s

#199

Qwen3-8B

8B

INT4

44 tok/s

~1.5s

#200

Gemma 3 4B

4B

INT4
Q8

77 tok/s

48 tok/s

~768 ms

~776 ms

#201

DeepSeek-R1 7B

7B

INT4
Q8

50 tok/s

27 tok/s

~1.3s

~1.5s

Inference Capacity

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

8B Models

8-bit

Q8

3B Models

16-bit

FP16

< 1B Models

Fine-Tuning Capacity

Hardware capacity for local training and adapter fine-tuning.

Context Length:

QLoRA

4-bit

8B Models

LoRA

16-bit

3B Models

Full Parameter Training

< 1B Models

Workload Recommendations

Guidance for optimal precision and operational ceilings on NVIDIA RTX 4060 (8GB).

Inference Sweet Spot

Recommended for lightweight models (1B to 3B) at FP16/Q8, and 7B/8B models at aggressive 4-bit quantizations.

Bandwidth & Speed Profile

With 272 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 60 tok/s on an 8B Q4 model and 7 tok/s on a 70B Q4 model.

Frequently Asked Questions