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NVIDIA RTX 5060 Ti (8GB)

The NVIDIA RTX 5060 Ti (8GB) features 8 GB of dedicated VRAM and 448 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

448 GB/s

Max Inference Class

8B Models (Q4)

TDP

180W

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 5060 Ti (8GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA RTX 5060 Ti (8GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#113

Qwen3.5-9B

9B

INT4

61 tok/s

~1.1s

#118

K2 Horizon 7B

7B

INT4

74 tok/s

~836 ms

#128

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8

20 tok/s

11 tok/s

~3.4s

~3.7s

#132

Qwen3.5-4B

4B

INT4
Q8

111 tok/s

73 tok/s

~492 ms

~497 ms

#146

Granite 4.2 8B

8B

INT4

67 tok/s

~950 ms

#150

Gemma 4 E4B

8B

INT4

67 tok/s

~950 ms

#169

OLMo 3 7B Think

7B

INT4

50 tok/s

~913 ms

#177

Gemma 3 12B

12B

INT4

43 tok/s

~1.7s

#182

Ministral 3 8B

8B

INT4

43 tok/s

~1.1s

#183

Qwen3.5-2B

2B

INT4
Q8
FP16

166 tok/s

119 tok/s

73 tok/s

~264 ms

~267 ms

~272 ms

#184

MiniCPM5-2B

2B

INT4
Q8
FP16

166 tok/s

119 tok/s

73 tok/s

~264 ms

~267 ms

~272 ms

#188

Gemma 4 E2B

5.1B

INT4
Q8

94 tok/s

57 tok/s

~618 ms

~678 ms

#189

Qwen3-4B

4B

INT4
Q8

111 tok/s

73 tok/s

~492 ms

~497 ms

#190

DeepSeek-R1 8B

8B

INT4

69 tok/s

~950 ms

#193

Ministral 3 3B

3B

INT4
Q8

89 tok/s

69 tok/s

~382 ms

~385 ms

#197

Gemma 2 9B

9B

INT4

61 tok/s

~1.1s

#198

Qwen2.5-7B

7B

INT4

74 tok/s

~836 ms

#199

Qwen3-8B

8B

INT4

67 tok/s

~950 ms

#200

Gemma 3 4B

4B

INT4
Q8

111 tok/s

73 tok/s

~492 ms

~497 ms

#201

DeepSeek-R1 7B

7B

INT4
Q8

76 tok/s

42 tok/s

~836 ms

~990 ms

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 5060 Ti (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 448 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 100 tok/s on an 8B Q4 model and 12 tok/s on a 70B Q4 model.

Frequently Asked Questions