Compare XPUs

Select up to 5 XPUs to compare side-by-side

Select XPUs to Compare

Showing 72 XPUs5 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 B200Tenstorrent WormholeNVIDIA H100 SXMAWS TrainiumHuawei Ascend 910B
ArchitectureBlackwellTensix CoreHopperInferentia/TrainiumDa Vinci
Form FactorSXMSXM
VRAM192 GB24 GB80 GB32 GB64 GB
Memory Bandwidth8,000 GB/s3,350 GB/s
TFLOPs (FP32)9067
TFLOPs (FP16)2,2501,979640
TFLOPs2,2503641,979190
TFLOPs (FP8)4,5003,958
TDP1000 W160 W700 W200 W400 W
Launch DateMar 2024Oct 2023Sep 2022Nov 2021Aug 2023

Efficiency Metrics

MetricB200WormholeH100 SXMTrainiumAscend 910B
TFLOPs per Watt (FP32-eq)1.131.141.410.47
Memory Bandwidth per GB41.7 GB/s41.9 GB/s

Performance Equivalence

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

To match 1x NVIDIA B200

Tenstorrent Wormhole
Compute (FP32-eq)
6.18x
Need 6.18x Wormhole
VRAM
8.00x
Need 8.00x Wormhole
NVIDIA H100 SXM
Compute (FP32-eq)
1.14x
Need 1.14x H100 SXM
FP32 Compute
1.34x
Need 1.34x H100 SXM
VRAM
2.40x
Need 2.40x H100 SXM
Memory Bandwidth
2.39x
Need 2.39x H100 SXM
AWS Trainium
Compute (FP32-eq)
11.84x
Need 11.84x Trainium
VRAM
6.00x
Need 6.00x Trainium
Huawei Ascend 910B
VRAM
3.00x
Need 3.00x Ascend 910B

To match 1x Tenstorrent Wormhole

NVIDIA B200
Compute (FP32-eq)
0.16x
B200 is 6.18x faster
VRAM
0.13x
B200 has 8.00x more
NVIDIA H100 SXM
Compute (FP32-eq)
0.18x
H100 SXM is 5.44x faster
VRAM
0.30x
H100 SXM has 3.33x more
AWS Trainium
Compute (FP32-eq)
1.92x
Need 1.92x Trainium
VRAM
0.75x
Trainium has 1.33x more
Huawei Ascend 910B
VRAM
0.38x
Ascend 910B has 2.67x more

To match 1x NVIDIA H100 SXM

NVIDIA B200
Compute (FP32-eq)
0.88x
B200 is 1.14x faster
FP32 Compute
0.74x
B200 is 1.34x faster
VRAM
0.42x
B200 has 2.40x more
Memory Bandwidth
0.42x
B200 has 2.39x more
Tenstorrent Wormhole
Compute (FP32-eq)
5.44x
Need 5.44x Wormhole
VRAM
3.33x
Need 3.33x Wormhole
AWS Trainium
Compute (FP32-eq)
10.42x
Need 10.42x Trainium
VRAM
2.50x
Need 2.50x Trainium
Huawei Ascend 910B
VRAM
1.25x
Need 1.25x Ascend 910B

To match 1x AWS Trainium

NVIDIA B200
Compute (FP32-eq)
0.08x
B200 is 11.84x faster
VRAM
0.17x
B200 has 6.00x more
Tenstorrent Wormhole
Compute (FP32-eq)
0.52x
Wormhole is 1.92x faster
VRAM
1.33x
Need 1.33x Wormhole
NVIDIA H100 SXM
Compute (FP32-eq)
0.10x
H100 SXM is 10.42x faster
VRAM
0.40x
H100 SXM has 2.50x more
Huawei Ascend 910B
VRAM
0.50x
Ascend 910B has 2.00x more

To match 1x Huawei Ascend 910B

NVIDIA B200
VRAM
0.33x
B200 has 3.00x more
Tenstorrent Wormhole
VRAM
2.67x
Need 2.67x Wormhole
NVIDIA H100 SXM
VRAM
0.80x
H100 SXM has 1.25x more
AWS Trainium
VRAM
2.00x
Need 2.00x Trainium

Pricing

Price TypeB200WormholeH100 SXMTrainiumAscend 910B
CAPEX (Street Price)$70,000$30,000
OPEX (per hour)$3.50/hr
Price per TFLOPs (FP32-eq)$62$30