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NVIDIA RTX A6000 (48GB)

The NVIDIA RTX A6000 (48GB) features 48 GB of dedicated VRAM and 768 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

768 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 A6000 (48GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA RTX A6000 (48GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#33

Qwen 3.8 27B

27B

INT4
Q8

38 tok/s

22 tok/s

~1.9s

~1.9s

#48

Agnes 3.0 Flash

33B

INT4
Q8

32 tok/s

18 tok/s

~2.3s

~2.4s

#72

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8

137 tok/s

100 tok/s

~380 ms

~383 ms

#83

Qwen3.5-27B

27B

INT4
Q8

38 tok/s

22 tok/s

~1.9s

~1.9s

#92

Sarvam-30B

32B (2.4B active)

INT4
Q8

169 tok/s

134 tok/s

~267 ms

~268 ms

#94

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8

155 tok/s

118 tok/s

~310 ms

~312 ms

#96

Muse Glimmer 30B

30B

INT4
Q8

35 tok/s

20 tok/s

~2.1s

~2.1s

#100

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

49 tok/s

34 tok/s

20 tok/s

~1.0s

~1.0s

~1.0s

#101

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

4 tok/s

2 tok/s

1 tok/s

~20.9s

~21.1s

~21.6s

#108

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8

145 tok/s

105 tok/s

~348 ms

~351 ms

#109

Gemma 4 12B

11.95B

INT4
Q8
FP16

56 tok/s

39 tok/s

23 tok/s

~872 ms

~879 ms

~898 ms

#113

Qwen3.5-9B

9B

INT4
Q8
FP16

93 tok/s

59 tok/s

33 tok/s

~658 ms

~664 ms

~678 ms

#114

Qwen3.5-35B-A3B

35B (3B active)

INT4
Q8

155 tok/s

118 tok/s

~310 ms

~312 ms

#118

K2 Horizon 7B

7B

INT4
Q8
FP16

111 tok/s

72 tok/s

41 tok/s

~516 ms

~521 ms

~532 ms

#128

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

33 tok/s

20 tok/s

10 tok/s

~2.1s

~2.1s

~2.1s

#129

Gemma 4 31B

30.7B

INT4
Q8

34 tok/s

20 tok/s

~2.2s

~2.2s

#131

Nemotron 3.5 Lightning

30B (3B active)

INT4
Q8

69 tok/s

63 tok/s

~313 ms

~314 ms

#132

Qwen3.5-4B

4B

INT4
Q8
FP16

157 tok/s

109 tok/s

65 tok/s

~305 ms

~308 ms

~314 ms

#133

Qwen3-30B-A3B

30B (3B active)

INT4
Q8

157 tok/s

119 tok/s

~305 ms

~307 ms

#136

GPT-OSS 20B

21B (3.6B active)

INT4
Q8
FP16

76 tok/s

66 tok/s

44 tok/s

~333 ms

~335 ms

~397 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 A6000 (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 768 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 171 tok/s on an 8B Q4 model and 20 tok/s on a 70B Q4 model.

Frequently Asked Questions