Compute Comparison
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Ampere

NVIDIA RTX 3090

wins

1

The RTX 3090 remains a popular budget option for AI workloads with 24GB GDDR6X.

Budget fine-tuningSmall model inferenceHobbyist AI

Ampere

NVIDIA A10

wins

3

The NVIDIA A10 is a versatile Ampere GPU with 24GB GDDR6 and 150W TDP.

InferenceGraphics renderingVirtual workstations

Performance comparison

Visual bars — winner highlighted

NVIDIA RTX 3090

Metric

NVIDIA A10

FP16 TFLOPS

71 T
125 T

Bandwidth

936 GB/s
600 GB/s

VRAM

246 GB
246 GB

TDP (lower=better)

350 W
150 W

TFLOPS/watt

0.20
0.83

GB/s per watt

2.67
4.00

Full specification table

SpecNVIDIA RTX 3090NVIDIA A10
ArchitectureAmpereAmpere
VRAM24 GB GDDR6X24 GB GDDR6
VRAM typeGDDR6XGDDR6
Memory bandwidth936 GB/s600 GB/s
FP16 TFLOPS71 TFLOPS125 TFLOPS
TDP350 W150 W
TFLOPS/watt0.20 T/W0.83 T/W
GB/s per watt2.67 GB/s/W4.00 GB/s/W
NVLinkNoNo
Release year20202021

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Power efficiency analysis

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

NVIDIA RTX 3090

FP16 TFLOPS71 TFLOPS
TDP350 W
TFLOPS/watt0.203 T/W
GB/s per watt2.67 GB/s/W

NVIDIA A10

FP16 TFLOPS125 TFLOPS
TDP150 W
TFLOPS/watt0.833 T/W
GB/s per watt4.00 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 RTX 3090 for:

  • Budget fine-tuning
  • Small model inference
  • Hobbyist AI

Choose NVIDIA A10 for:

  • Inference
  • Graphics rendering
  • Virtual workstations