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NVIDIA L40S (48GB)

The NVIDIA L40S (48GB) features 48 GB of dedicated VRAM and 864 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

864 GB/s

Max Inference Class

32B Models (Q4)

TDP

350W

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 L40S (48GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA L40S (48GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#33

Qwen 3.8 27B

27B

INT4
Q8

42 tok/s

24 tok/s

~944 ms

~962 ms

#48

Agnes 3.0 Flash

33B

INT4
Q8

35 tok/s

20 tok/s

~1.1s

~1.2s

#72

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8

171 tok/s

119 tok/s

~187 ms

~190 ms

#83

Qwen3.5-27B

27B

INT4
Q8

42 tok/s

24 tok/s

~944 ms

~962 ms

#92

Sarvam-30B

32B (2.4B active)

INT4
Q8

221 tok/s

166 tok/s

~131 ms

~133 ms

#94

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8

199 tok/s

144 tok/s

~153 ms

~155 ms

#96

Muse Glimmer 30B

30B

INT4
Q8

38 tok/s

22 tok/s

~1.0s

~1.1s

#100

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

55 tok/s

37 tok/s

21 tok/s

~503 ms

~511 ms

~532 ms

#101

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

4 tok/s

2 tok/s

1 tok/s

~10.3s

~10.5s

~11.0s

#108

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8

183 tok/s

126 tok/s

~171 ms

~174 ms

#109

Gemma 4 12B

11.95B

INT4
Q8
FP16

63 tok/s

43 tok/s

25 tok/s

~431 ms

~438 ms

~456 ms

#113

Qwen3.5-9B

9B

INT4
Q8
FP16

110 tok/s

67 tok/s

36 tok/s

~323 ms

~329 ms

~342 ms

#114

Qwen3.5-35B-A3B

35B (3B active)

INT4
Q8

199 tok/s

144 tok/s

~153 ms

~155 ms

#118

K2 Horizon 7B

7B

INT4
Q8
FP16

135 tok/s

83 tok/s

45 tok/s

~254 ms

~258 ms

~268 ms

#128

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

36 tok/s

21 tok/s

11 tok/s

~1.0s

~1.0s

~1.1s

#129

Gemma 4 31B

30.7B

INT4
Q8

37 tok/s

21 tok/s

~1.1s

~1.1s

#131

Nemotron 3.5 Lightning

30B (3B active)

INT4
Q8

79 tok/s

71 tok/s

~158 ms

~159 ms

#132

Qwen3.5-4B

4B

INT4
Q8
FP16

201 tok/s

132 tok/s

75 tok/s

~150 ms

~153 ms

~158 ms

#133

Qwen3-30B-A3B

30B (3B active)

INT4
Q8

201 tok/s

146 tok/s

~150 ms

~152 ms

#136

GPT-OSS 20B

21B (3.6B active)

INT4
Q8
FP16

88 tok/s

76 tok/s

49 tok/s

~167 ms

~168 ms

~203 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 L40S (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 864 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 192 tok/s on an 8B Q4 model and 23 tok/s on a 70B Q4 model.

Frequently Asked Questions