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Showing 72 XPUs • 3 selected

Alibaba

Hanguang 800

AMD

MI100

23.1 TFLOPs

AMD

MI210

181 TFLOPs

AMD

MI250X

383 TFLOPs

AMD

MI300A

980.6 TFLOPs

AMD

MI300X

1,307 TFLOPs

AMD

MI325X

1,400 TFLOPs

AMD

MI350X

2,100 TFLOPs

AMD

Radeon PRO W7900

122 TFLOPs

AMD

Radeon RX 7900 XT

104 TFLOPs

AMD

Radeon RX 7900 XTX

122 TFLOPs

AWS

Inferentia2

190 TFLOPs

AWS

Trainium

190 TFLOPs

AWS

Trainium2

680 TFLOPs

Baidu

Kunlun II

Biren Technology

BR100

Cambricon

MLU370

256 TFLOPs

Cerebras

WSE-3

Enflame Technology

CloudBlazer T20

Etched

Sohu

10,000 TFLOPs

FuriosaAI

Warboy

Google

TPU v4

275 TFLOPs

Google

TPU v5e

197 TFLOPs

Google

TPU v5p

459 TFLOPs

Google

TPU v6e (Trillium)

918 TFLOPs

Graphcore

Bow IPU

Graphcore

IPU-M2000

Groq

LPU Inference Engine

Huawei

Ascend 910B

Iluvatar CoreX

BI-V150

300 TFLOPs

Intel

Data Center GPU Max 1100

177 TFLOPs

Intel

Data Center GPU Max 1550

419 TFLOPs

Intel Habana

Gaudi 2

432 TFLOPs

Intel Habana

Gaudi 3

1,835 TFLOPs

Multi-Metric Comparison

Relative performance across 5 key metrics (normalized to 100 = best in comparison)

Compute Performance (BF16)

Memory Capacity

Power Consumption

Power Efficiency

Specifications

Specification	NVIDIA A10	NVIDIA GeForce RTX 4080 Super	NVIDIA RTX 5000 Ada Generation
Architecture	Ampere	Ada Lovelace	Ada Lovelace
Form Factor	PCIe	PCIe	PCIe
VRAM	24 GB	16 GB	32 GB
Memory Bandwidth	600 GB/s	736 GB/s	576 GB/s
TFLOPs (FP32)	31.2	52.2	65.3
TFLOPs (FP16)	125	104.4	130.6
TFLOPs	125	104.4	130.6
TFLOPs (FP8)	—	—	—
TDP	150 W	320 W	250 W
Launch Date	Apr 2021	Jan 2024	Aug 2023

Efficiency Metrics

Metric	A10	GeForce RTX 4080 Super	RTX 5000 Ada Generation
TFLOPs per Watt (FP32-eq)	0.42	0.16	0.26
Memory Bandwidth per GB	25.0 GB/s	46.0 GB/s	18.0 GB/s

Performance Equivalence

How many units of each GPU are needed to match the performance of the others?

To match 1x NVIDIA A10

NVIDIA GeForce RTX 4080 Super

Compute (FP32-eq)

1.20x

Need 1.20x GeForce RTX 4080 Super

FP32 Compute

0.60x

GeForce RTX 4080 Super is 1.67x faster

VRAM

1.50x

Need 1.50x GeForce RTX 4080 Super

Memory Bandwidth

0.82x

GeForce RTX 4080 Super has 1.23x more

NVIDIA RTX 5000 Ada Generation

Compute (FP32-eq)

0.96x

RTX 5000 Ada Generation is 1.04x faster

FP32 Compute

0.48x

RTX 5000 Ada Generation is 2.09x faster

VRAM

0.75x

RTX 5000 Ada Generation has 1.33x more

Memory Bandwidth

1.04x

Need 1.04x RTX 5000 Ada Generation

To match 1x NVIDIA GeForce RTX 4080 Super

NVIDIA A10

Compute (FP32-eq)

0.84x

A10 is 1.20x faster

FP32 Compute

1.67x

Need 1.67x A10

VRAM

0.67x

A10 has 1.50x more

Memory Bandwidth

1.23x

Need 1.23x A10

NVIDIA RTX 5000 Ada Generation

Compute (FP32-eq)

0.80x

RTX 5000 Ada Generation is 1.25x faster

FP32 Compute

0.80x

RTX 5000 Ada Generation is 1.25x faster

VRAM

0.50x

RTX 5000 Ada Generation has 2.00x more

Memory Bandwidth

1.28x

Need 1.28x RTX 5000 Ada Generation

To match 1x NVIDIA RTX 5000 Ada Generation

NVIDIA A10

Compute (FP32-eq)

1.04x

Need 1.04x A10

FP32 Compute

2.09x

Need 2.09x A10

VRAM

1.33x

Need 1.33x A10

Memory Bandwidth

0.96x

A10 has 1.04x more

NVIDIA GeForce RTX 4080 Super

Compute (FP32-eq)

1.25x

Need 1.25x GeForce RTX 4080 Super

FP32 Compute

1.25x

Need 1.25x GeForce RTX 4080 Super

VRAM

2.00x

Need 2.00x GeForce RTX 4080 Super

Memory Bandwidth

0.78x

GeForce RTX 4080 Super has 1.28x more

Pricing

Price Type	A10	GeForce RTX 4080 Super	RTX 5000 Ada Generation
CAPEX (Street Price)	—	—	—
OPEX (per hour)	—	—	—
Price per TFLOPs (FP32-eq)	—	—	—