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NVIDIA RTX 5000 Blackwell (48GB)

The NVIDIA RTX 5000 Blackwell (48GB) features 48 GB of dedicated VRAM and 1344 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

1344 GB/s

Max Inference Class

32B Models (Q4)

TDP

250W

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 5000 Blackwell (48GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA RTX 5000 Blackwell (48GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#33

Qwen 3.8 27B

27B

INT4
Q8

62 tok/s

37 tok/s

~1.1s

~1.1s

#48

Agnes 3.0 Flash

33B

INT4
Q8

52 tok/s

31 tok/s

~1.4s

~1.4s

#72

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8

188 tok/s

146 tok/s

~224 ms

~226 ms

#83

Qwen3.5-27B

27B

INT4
Q8

62 tok/s

37 tok/s

~1.1s

~1.1s

#92

Sarvam-30B

32B (2.4B active)

INT4
Q8

221 tok/s

184 tok/s

~158 ms

~159 ms

#94

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8

207 tok/s

167 tok/s

~183 ms

~184 ms

#96

Muse Glimmer 30B

30B

INT4
Q8

57 tok/s

34 tok/s

~1.2s

~1.3s

#100

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

79 tok/s

55 tok/s

33 tok/s

~594 ms

~599 ms

~611 ms

#101

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

7 tok/s

4 tok/s

2 tok/s

~12.2s

~12.3s

~12.6s

#108

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8

196 tok/s

152 tok/s

~205 ms

~207 ms

#109

Gemma 4 12B

11.95B

INT4
Q8
FP16

88 tok/s

63 tok/s

38 tok/s

~509 ms

~514 ms

~524 ms

#113

Qwen3.5-9B

9B

INT4
Q8
FP16

137 tok/s

92 tok/s

53 tok/s

~385 ms

~389 ms

~397 ms

#114

Qwen3.5-35B-A3B

35B (3B active)

INT4
Q8

207 tok/s

167 tok/s

~183 ms

~184 ms

#118

K2 Horizon 7B

7B

INT4
Q8
FP16

159 tok/s

110 tok/s

66 tok/s

~303 ms

~306 ms

~312 ms

#128

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

54 tok/s

33 tok/s

18 tok/s

~1.2s

~1.2s

~1.2s

#129

Gemma 4 31B

30.7B

INT4
Q8

56 tok/s

33 tok/s

~1.3s

~1.3s

#131

Nemotron 3.5 Lightning

30B (3B active)

INT4
Q8

105 tok/s

97 tok/s

~185 ms

~185 ms

#132

Qwen3.5-4B

4B

INT4
Q8
FP16

208 tok/s

157 tok/s

101 tok/s

~180 ms

~182 ms

~186 ms

#133

Qwen3-30B-A3B

30B (3B active)

INT4
Q8

208 tok/s

168 tok/s

~180 ms

~181 ms

#136

GPT-OSS 20B

21B (3.6B active)

INT4
Q8
FP16

115 tok/s

102 tok/s

70 tok/s

~196 ms

~197 ms

~234 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 5000 Blackwell (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 1344 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 299 tok/s on an 8B Q4 model and 35 tok/s on a 70B Q4 model.

Frequently Asked Questions