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Ada Lovelace

NVIDIA L40S

wins

0

The L40S is NVIDIA's inference-optimized Ada Lovelace GPU. 48GB GDDR6 and 362 TFLOPS FP16 make it a strong choice for production inference at lower cost than H100.

InferenceVideo AIMulti-modal workloads

Ada Lovelace

NVIDIA RTX 6000 Ada

wins

4

The RTX 6000 Ada is NVIDIA's professional workstation GPU with 48GB GDDR6 and 364 TFLOPS FP16.

Professional inferenceFine-tuningWorkstation AI

Performance comparison

Visual bars — winner highlighted

NVIDIA L40S

Metric

NVIDIA RTX 6000 Ada

FP16 TFLOPS

362 T
364 T

Bandwidth

864 GB/s
960 GB/s

VRAM

486 GB
486 GB

TDP (lower=better)

350 W
300 W

TFLOPS/watt

1.03
1.21

GB/s per watt

2.47
3.20

Full specification table

SpecNVIDIA L40SNVIDIA RTX 6000 Ada
ArchitectureAda LovelaceAda Lovelace
VRAM48 GB GDDR648 GB GDDR6
VRAM typeGDDR6GDDR6
Memory bandwidth864 GB/s960 GB/s
FP16 TFLOPS362 TFLOPS364 TFLOPS
TDP350 W300 W
TFLOPS/watt1.03 T/W1.21 T/W
GB/s per watt2.47 GB/s/W3.20 GB/s/W
NVLinkNoNo
Release year20232022

Live cloud pricing

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Power efficiency analysis

TFLOPS/watt and GB/s/watt — critical for data center TCO

NVIDIA L40S

FP16 TFLOPS362 TFLOPS
TDP350 W
TFLOPS/watt1.034 T/W
GB/s per watt2.47 GB/s/W

NVIDIA RTX 6000 Ada

FP16 TFLOPS364 TFLOPS
TDP300 W
TFLOPS/watt1.213 T/W
GB/s per watt3.20 GB/s/W

TFLOPS/watt measures compute efficiency — how much AI throughput you get per watt of power consumed. For data centers with PUE of 1.2–1.5, a 10% improvement in TFLOPS/watt translates directly to lower electricity costs and cooling requirements. GB/s/watt measures memory bandwidth efficiency, which is the binding constraint for memory-bound LLM inference workloads.

When to choose each GPU

Choose NVIDIA L40S for:

  • Inference
  • Video AI
  • Multi-modal workloads

Choose NVIDIA RTX 6000 Ada for:

  • Professional inference
  • Fine-tuning
  • Workstation AI