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NVIDIA RTX 6000 Ada Generation (48GB)

The NVIDIA RTX 6000 Ada Generation (48GB) features 48 GB of dedicated VRAM and 960 GB/s memory bandwidth, supporting CUDA and TensorRT-LLM runtimes for full-precision and quantized inference.

Memory

48 GB

Usable Memory Ceiling

48 GB

Bandwidth

960 GB/s

Max Inference Class

32B Models (Q4)

TDP

300W

VRAM Scaling by Context Length

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

DeepSeek-R1 7B (7B)Sahabat-AI-Gemma2-9B (9.2B)OLMo 3.1 32B Think (32B)Ling 3.0 Flash VL (124B (5.5B active))

Precision:

Best Models to Run on NVIDIA RTX 6000 Ada Generation (48GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA RTX 6000 Ada Generation (48GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#33

Qwen 3.8 27B

27B

INT4
Q8

46 tok/s

27 tok/s

~836 ms

~851 ms

#48

Agnes 3.0 Flash

33B

INT4
Q8

39 tok/s

23 tok/s

~1.0s

~1.0s

#72

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8

157 tok/s

117 tok/s

~169 ms

~171 ms

#83

Qwen3.5-27B

27B

INT4
Q8

46 tok/s

27 tok/s

~836 ms

~851 ms

#92

Sarvam-30B

32B (2.4B active)

INT4
Q8

190 tok/s

153 tok/s

~120 ms

~121 ms

#94

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8

176 tok/s

137 tok/s

~139 ms

~140 ms

#96

Muse Glimmer 30B

30B

INT4
Q8

42 tok/s

25 tok/s

~926 ms

~943 ms

#100

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

60 tok/s

41 tok/s

24 tok/s

~447 ms

~454 ms

~472 ms

#101

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

5 tok/s

3 tok/s

1 tok/s

~9.1s

~9.3s

~9.6s

#108

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8

165 tok/s

123 tok/s

~155 ms

~157 ms

#109

Gemma 4 12B

11.95B

INT4
Q8
FP16

67 tok/s

47 tok/s

28 tok/s

~384 ms

~390 ms

~405 ms

#113

Qwen3.5-9B

9B

INT4
Q8
FP16

110 tok/s

71 tok/s

40 tok/s

~289 ms

~294 ms

~305 ms

#114

Qwen3.5-35B-A3B

35B (3B active)

INT4
Q8

176 tok/s

137 tok/s

~139 ms

~140 ms

#118

K2 Horizon 7B

7B

INT4
Q8
FP16

130 tok/s

86 tok/s

50 tok/s

~228 ms

~232 ms

~240 ms

#128

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

40 tok/s

24 tok/s

13 tok/s

~899 ms

~915 ms

~952 ms

#129

Gemma 4 31B

30.7B

INT4
Q8

42 tok/s

24 tok/s

~947 ms

~964 ms

#131

Nemotron 3.5 Lightning

30B (3B active)

INT4
Q8

82 tok/s

75 tok/s

~143 ms

~144 ms

#132

Qwen3.5-4B

4B

INT4
Q8
FP16

177 tok/s

127 tok/s

78 tok/s

~137 ms

~139 ms

~144 ms

#133

Qwen3-30B-A3B

30B (3B active)

INT4
Q8

177 tok/s

138 tok/s

~136 ms

~138 ms

#136

GPT-OSS 20B

21B (3.6B active)

INT4
Q8
FP16

90 tok/s

79 tok/s

53 tok/s

~151 ms

~152 ms

~182 ms

Inference Capacity

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

32B Models

8-bit

Q8

32B Models

16-bit

FP16

14B Models

Fine-Tuning Capacity

Hardware capacity for local training and adapter fine-tuning.

Context Length:

QLoRA

4-bit

32B Models

LoRA

16-bit

14B Models

Full Parameter Training

7B-8B Models

Workload Recommendations

Guidance for optimal precision and operational ceilings on NVIDIA RTX 6000 Ada Generation (48GB).

Inference Sweet Spot

Optimized for 14B models at uncompressed or Q8 precision, and 32B models at Q4 with up to 32k context.

Bandwidth & Speed Profile

With 960 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 213 tok/s on an 8B Q4 model and 25 tok/s on a 70B Q4 model.

Frequently Asked Questions