Compare XPUs

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Showing 72 XPUs • 5 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

Meta

MTIA v1

Microsoft

Maia 100

700 TFLOPs

Moore Threads

MTT S80

NVIDIA

A10

125 TFLOPs

NVIDIA

A100 SXM

312 TFLOPs

NVIDIA

A40

150 TFLOPs

NVIDIA

B200

2,250 TFLOPs

NVIDIA

GB200 NVL72

360,000 TFLOPs

NVIDIA

GB200 Superchip

5,000 TFLOPs

NVIDIA

GeForce RTX 4060 Ti

44.2 TFLOPs

NVIDIA

GeForce RTX 4070

58.2 TFLOPs

NVIDIA

GeForce RTX 4070 Super

71 TFLOPs

NVIDIA

GeForce RTX 4070 Ti

80.2 TFLOPs

NVIDIA

GeForce RTX 4070 Ti Super

88.2 TFLOPs

NVIDIA

GeForce RTX 4080

97.5 TFLOPs

NVIDIA

GeForce RTX 4080 Super

104.4 TFLOPs

NVIDIA

GeForce RTX 4090

165.2 TFLOPs

NVIDIA

GeForce RTX 5070

61.6 TFLOPs

NVIDIA

GeForce RTX 5070 Ti

88 TFLOPs

NVIDIA

GeForce RTX 5080

112.6 TFLOPs

NVIDIA

GeForce RTX 5090

209.5 TFLOPs

NVIDIA

H100 PCIe

1,513 TFLOPs

NVIDIA

H100 SXM

1,979 TFLOPs

NVIDIA

H200 PCIe

1,513 TFLOPs

NVIDIA

H200 SXM

1,979 TFLOPs

NVIDIA

L4

121 TFLOPs

NVIDIA

L40S

733 TFLOPs

NVIDIA

RTX 4000 Ada Generation

53.4 TFLOPs

NVIDIA

RTX 5000 Ada Generation

130.6 TFLOPs

NVIDIA

RTX 6000 Ada Generation

182.2 TFLOPs

NVIDIA

RTX PRO 6000 Blackwell Max-Q

125 TFLOPs

NVIDIA

RTX PRO 6000 Blackwell Server Edition

250 TFLOPs

NVIDIA

RTX PRO 6000 Blackwell Workstation Edition

250 TFLOPs

Qualcomm

Cloud AI 100

50 TFLOPs

Rebellions

ATOM

SambaNova

SN40L

Tenstorrent

Grayskull

200 TFLOPs

Tenstorrent

Wormhole

364 TFLOPs

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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

SpecificationNVIDIA L4NVIDIA A40AWS Trainium2NVIDIA H100 SXMBaidu Kunlun II
ArchitectureAda LovelaceAmpereTrainium Gen2HopperKunlun Core
Form FactorPCIePCIe—SXM—
VRAM24 GB48 GB—80 GB32 GB
Memory Bandwidth300 GB/s696 GB/s—3,350 GB/s—
TFLOPs (FP32)30.337.4—67—
TFLOPs (FP16)242150—1,979256
TFLOPs1211506801,979—
TFLOPs (FP8)485——3,958—
TDP72 W300 W300 W700 W200 W
Launch DateMar 2023Oct 2020Nov 2023Sep 2022Aug 2021

Efficiency Metrics

MetricL4A40Trainium2H100 SXMKunlun II
TFLOPs per Watt (FP32-eq)0.840.251.131.41—
Memory Bandwidth per GB12.5 GB/s14.5 GB/s—41.9 GB/s—

Performance Equivalence

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

To match 1x NVIDIA L4

NVIDIA A40
Compute (FP32-eq)
0.81x
A40 is 1.24x faster
FP32 Compute
0.81x
A40 is 1.23x faster
VRAM
0.50x
A40 has 2.00x more
Memory Bandwidth
0.43x
A40 has 2.32x more
AWS Trainium2
Compute (FP32-eq)
0.18x
Trainium2 is 5.62x faster
NVIDIA H100 SXM
Compute (FP32-eq)
0.06x
H100 SXM is 16.36x faster
FP32 Compute
0.45x
H100 SXM is 2.21x faster
VRAM
0.30x
H100 SXM has 3.33x more
Memory Bandwidth
0.09x
H100 SXM has 11.17x more
Baidu Kunlun II
VRAM
0.75x
Kunlun II has 1.33x more

To match 1x NVIDIA A40

NVIDIA L4
Compute (FP32-eq)
1.24x
Need 1.24x L4
FP32 Compute
1.23x
Need 1.23x L4
VRAM
2.00x
Need 2.00x L4
Memory Bandwidth
2.32x
Need 2.32x L4
AWS Trainium2
Compute (FP32-eq)
0.22x
Trainium2 is 4.53x faster
NVIDIA H100 SXM
Compute (FP32-eq)
0.08x
H100 SXM is 13.19x faster
FP32 Compute
0.56x
H100 SXM is 1.79x faster
VRAM
0.60x
H100 SXM has 1.67x more
Memory Bandwidth
0.21x
H100 SXM has 4.81x more
Baidu Kunlun II
VRAM
1.50x
Need 1.50x Kunlun II

To match 1x AWS Trainium2

NVIDIA L4
Compute (FP32-eq)
5.62x
Need 5.62x L4
NVIDIA A40
Compute (FP32-eq)
4.53x
Need 4.53x A40
NVIDIA H100 SXM
Compute (FP32-eq)
0.34x
H100 SXM is 2.91x faster

To match 1x NVIDIA H100 SXM

NVIDIA L4
Compute (FP32-eq)
16.36x
Need 16.36x L4
FP32 Compute
2.21x
Need 2.21x L4
VRAM
3.33x
Need 3.33x L4
Memory Bandwidth
11.17x
Need 11.17x L4
NVIDIA A40
Compute (FP32-eq)
13.19x
Need 13.19x A40
FP32 Compute
1.79x
Need 1.79x A40
VRAM
1.67x
Need 1.67x A40
Memory Bandwidth
4.81x
Need 4.81x A40
AWS Trainium2
Compute (FP32-eq)
2.91x
Need 2.91x Trainium2
Baidu Kunlun II
VRAM
2.50x
Need 2.50x Kunlun II

To match 1x Baidu Kunlun II

NVIDIA L4
VRAM
1.33x
Need 1.33x L4
NVIDIA A40
VRAM
0.67x
A40 has 1.50x more
NVIDIA H100 SXM
VRAM
0.40x
H100 SXM has 2.50x more

Pricing

Price TypeL4A40Trainium2H100 SXMKunlun II
CAPEX (Street Price)$4,000——$30,000—
OPEX (per hour)$0.80/hr—$1.34/hr$3.50/hr—
Price per TFLOPs (FP32-eq)$66——$30—