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NVIDIA RTX 2000 Ada Generation (16GB)

The NVIDIA RTX 2000 Ada Generation (16GB) features 16 GB of dedicated VRAM and 224 GB/s memory bandwidth, supporting CUDA and TensorRT-LLM runtimes for full-precision and quantized inference.

Memory

16 GB

Usable Memory Ceiling

16 GB

Bandwidth

224 GB/s

Max Inference Class

14B Models (Q4)

TDP

70W

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)ChatGLM2-6B (6B)Mellum 2.1 12B A2.5B Thinking (12B (2.5B active))Mixtral-8x7B-v0.1 (46.7B (7B active))

Precision:

Best Models to Run on NVIDIA RTX 2000 Ada Generation (16GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA RTX 2000 Ada Generation (16GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#36

Qwen 3.8 27B

27B

INT4

11 tok/s

~7.2s

#86

Qwen3.5-27B

27B

INT4

11 tok/s

~7.2s

#102

Phi-4 Reasoning Plus

14B

INT4

16 tok/s

~3.3s

#105

MiMo V2 Flash

15B (309B active)

INT4

1 tok/s

~73.0s

#110

Gemma 4 26B A4B

25.2B (3.8B active)

INT4

55 tok/s

~1.2s

#121

Qwen3.5-9B

9B

INT4
Q8

33 tok/s

19 tok/s

~2.1s

~2.1s

#127

K2 Horizon 7B

7B

INT4
Q8
FP16

41 tok/s

24 tok/s

12 tok/s

~1.6s

~1.7s

~2.0s

#130

Gemma 4 12B

11.95B

INT4
Q8

18 tok/s

11 tok/s

~2.8s

~3.3s

#136

Qwen3.5-4B

4B

INT4
Q8
FP16

65 tok/s

40 tok/s

22 tok/s

~963 ms

~973 ms

~994 ms

#139

GPT-OSS 20B

21B (3.6B active)

INT4

23 tok/s

~1.2s

#140

GLM-4V

9B

INT4
Q8

23 tok/s

15 tok/s

~2.1s

~2.3s

#145

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

10 tok/s

6 tok/s

3 tok/s

~6.6s

~6.7s

~6.8s

#152

Granite 4.2 8B

8B

INT4
Q8

37 tok/s

22 tok/s

~1.9s

~1.9s

#157

Gemma 4 E4B

8B

INT4
Q8

37 tok/s

22 tok/s

~1.9s

~1.9s

#163

Gemma 3 27B

27B

INT4

11 tok/s

~7.2s

#164

Phi-4

14B

INT4
Q8

22 tok/s

11 tok/s

~3.2s

~3.8s

#176

DeepSeek-R1 14B

14B

INT4
Q8

23 tok/s

12 tok/s

~3.2s

~3.8s

#177

Ministral 3 14B

14B

INT4

16 tok/s

~3.3s

#180

Gemma 3 12B

12B

INT4
Q8

26 tok/s

14 tok/s

~2.8s

~3.0s

#184

Mistral-Small-2501

24B

INT4

13 tok/s

~5.9s

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 2000 Ada Generation (16GB).

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 224 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 50 tok/s on an 8B Q4 model and 6 tok/s on a 70B Q4 model.

Frequently Asked Questions