Compare XPUs

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

Select XPUs to Compare

Showing 72 XPUs4 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

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

SpecificationAMD MI100AMD MI300AGoogle TPU v6e (Trillium)Etched Sohu
ArchitectureCDNACDNA 3TrilliumTransformer ASIC
Form FactorPCIeOAMCustomPCIe
VRAM32 GB128 GB32 GB144 GB
Memory Bandwidth1,228 GB/s5,300 GB/s1,600 GB/s4,800 GB/s
TFLOPs (FP32)23.1122.645910,000
TFLOPs (FP16)184.6980.6918
TFLOPs23.1980.691810,000
TFLOPs (FP8)
TDP300 W760 W200 W700 W
Launch DateNov 2020Dec 2023May 2024Jun 2024

Efficiency Metrics

MetricMI100MI300ATPU v6e (Trillium)Sohu
TFLOPs per Watt (FP32-eq)0.080.652.2914.29
Memory Bandwidth per GB38.4 GB/s41.4 GB/s50.0 GB/s33.3 GB/s

Performance Equivalence

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

To match 1x AMD MI100

AMD MI300A
Compute (FP32-eq)
0.05x
MI300A is 21.23x faster
FP32 Compute
0.19x
MI300A is 5.31x faster
VRAM
0.25x
MI300A has 4.00x more
Memory Bandwidth
0.23x
MI300A has 4.32x more
Google TPU v6e (Trillium)
Compute (FP32-eq)
0.05x
TPU v6e (Trillium) is 19.87x faster
FP32 Compute
0.05x
TPU v6e (Trillium) is 19.87x faster
VRAM
1.00x
TPU v6e (Trillium) has 1.00x more
Memory Bandwidth
0.77x
TPU v6e (Trillium) has 1.30x more
Etched Sohu
Compute (FP32-eq)
0.00x
Sohu is 432.90x faster
FP32 Compute
0.00x
Sohu is 432.90x faster
VRAM
0.22x
Sohu has 4.50x more
Memory Bandwidth
0.26x
Sohu has 3.91x more

To match 1x AMD MI300A

AMD MI100
Compute (FP32-eq)
21.23x
Need 21.23x MI100
FP32 Compute
5.31x
Need 5.31x MI100
VRAM
4.00x
Need 4.00x MI100
Memory Bandwidth
4.32x
Need 4.32x MI100
Google TPU v6e (Trillium)
Compute (FP32-eq)
1.07x
Need 1.07x TPU v6e (Trillium)
FP32 Compute
0.27x
TPU v6e (Trillium) is 3.74x faster
VRAM
4.00x
Need 4.00x TPU v6e (Trillium)
Memory Bandwidth
3.31x
Need 3.31x TPU v6e (Trillium)
Etched Sohu
Compute (FP32-eq)
0.05x
Sohu is 20.40x faster
FP32 Compute
0.01x
Sohu is 81.57x faster
VRAM
0.89x
Sohu has 1.13x more
Memory Bandwidth
1.10x
Need 1.10x Sohu

To match 1x Google TPU v6e (Trillium)

AMD MI100
Compute (FP32-eq)
19.87x
Need 19.87x MI100
FP32 Compute
19.87x
Need 19.87x MI100
VRAM
1.00x
MI100 has 1.00x more
Memory Bandwidth
1.30x
Need 1.30x MI100
AMD MI300A
Compute (FP32-eq)
0.94x
MI300A is 1.07x faster
FP32 Compute
3.74x
Need 3.74x MI300A
VRAM
0.25x
MI300A has 4.00x more
Memory Bandwidth
0.30x
MI300A has 3.31x more
Etched Sohu
Compute (FP32-eq)
0.05x
Sohu is 21.79x faster
FP32 Compute
0.05x
Sohu is 21.79x faster
VRAM
0.22x
Sohu has 4.50x more
Memory Bandwidth
0.33x
Sohu has 3.00x more

To match 1x Etched Sohu

AMD MI100
Compute (FP32-eq)
432.90x
Need 432.90x MI100
FP32 Compute
432.90x
Need 432.90x MI100
VRAM
4.50x
Need 4.50x MI100
Memory Bandwidth
3.91x
Need 3.91x MI100
AMD MI300A
Compute (FP32-eq)
20.40x
Need 20.40x MI300A
FP32 Compute
81.57x
Need 81.57x MI300A
VRAM
1.13x
Need 1.13x MI300A
Memory Bandwidth
0.91x
MI300A has 1.10x more
Google TPU v6e (Trillium)
Compute (FP32-eq)
21.79x
Need 21.79x TPU v6e (Trillium)
FP32 Compute
21.79x
Need 21.79x TPU v6e (Trillium)
VRAM
4.50x
Need 4.50x TPU v6e (Trillium)
Memory Bandwidth
3.00x
Need 3.00x TPU v6e (Trillium)

Pricing

Price TypeMI100MI300ATPU v6e (Trillium)Sohu
CAPEX (Street Price)
OPEX (per hour)
Price per TFLOPs (FP32-eq)