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NVIDIA RTX 3070 Ti (8GB)

The NVIDIA RTX 3070 Ti (8GB) features 8 GB of dedicated VRAM and 608 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

608 GB/s

Max Inference Class

8B Models (Q4)

TDP

290W

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)Phi-2 (2.7B)Mistral-7B-v0.1 (7.3B)ERNIE-4.5-21B-A3B-Base (21B (3B active))

Precision:

Best Models to Run on NVIDIA RTX 3070 Ti (8GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA RTX 3070 Ti (8GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#125

Qwen3.5-9B

9B

INT4

78 tok/s

~1.2s

#128

K2 Horizon 7B

7B

INT4

94 tok/s

~906 ms

#140

Qwen3.5-4B

4B

INT4
Q8

136 tok/s

92 tok/s

~533 ms

~537 ms

#150

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8

27 tok/s

15 tok/s

~3.6s

~4.0s

#158

Granite 4.2 8B

8B

INT4

85 tok/s

~1.0s

#159

Gemma 4 E4B

8B

INT4

85 tok/s

~1.0s

#178

OLMo 3 7B Think

7B

INT4

65 tok/s

~988 ms

#186

Gemma 3 12B

12B

INT4

56 tok/s

~1.8s

#189

Ministral 3 8B

8B

INT4

56 tok/s

~1.2s

#191

MiniCPM5-2B

2B

INT4
Q8
FP16

194 tok/s

145 tok/s

93 tok/s

~286 ms

~288 ms

~292 ms

#192

Qwen3.5-2B

2B

INT4
Q8
FP16

194 tok/s

145 tok/s

93 tok/s

~286 ms

~288 ms

~292 ms

#200

Gemma 4 E2B

5.1B

INT4
Q8

117 tok/s

73 tok/s

~670 ms

~732 ms

#202

DeepSeek-R1 8B

8B

INT4

87 tok/s

~1.0s

#204

Qwen3-4B

4B

INT4
Q8

136 tok/s

92 tok/s

~533 ms

~537 ms

#205

Ministral 3 3B

3B

INT4
Q8

112 tok/s

88 tok/s

~412 ms

~414 ms

#207

Gemma 2 9B

9B

INT4

78 tok/s

~1.2s

#208

Qwen3.5-0.8B

0.8B

INT4
Q8
FP16

271 tok/s

228 tok/s

169 tok/s

~120 ms

~121 ms

~122 ms

#210

Gemma 3 4B

4B

INT4
Q8

136 tok/s

92 tok/s

~533 ms

~537 ms

#211

Qwen3-8B

8B

INT4

85 tok/s

~1.0s

#213

DeepSeek-R1 7B

7B

INT4
Q8

96 tok/s

54 tok/s

~906 ms

~1.1s

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 3070 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 608 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 135 tok/s on an 8B Q4 model and 16 tok/s on a 70B Q4 model.

Frequently Asked Questions