NVIDIA H100 SXM5 80 GB vs SPARKLE Arc A310 OmniView

Comparison of NVIDIA H100 SXM5 80 GB with 80 GB HBM3 and 16,896 cores vs SPARKLE Arc A310 OmniView with 4 GB GDDR6 and 768 cores.

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Performance Rating

H200 H200
MI325X MI325X
A100 A100

NVIDIA H100 SXM5 80 GB

56.4

NVIDIA H100 SXM5 80 GB

56.4
RX 7900 XTX RX 7900 XTX
Instinct MI300X Instinct MI300X
MI250 MI250

SPARKLE Arc A310 OmniView

SPARKLE Arc A310 OmniView

Contents:

Memory ML Performance Compute Power Architecture & Compatibility ML Software Support Clocks & Performance Power Consumption Rendering Benchmarks Additional

Memory

Memory Size

🔥 +1,900% 80 ГБ
4 GB

Memory Type

HBM3 GDDR6

Memory Bandwidth

🔥 3.36 TB/s
124.0 GB/s

Memory Bus Width

5,120 бит 64 бит

ML Performance

FP16 (Half Precision)

🔥 +4,255% 267.6 TFLOPS
6.144 TFLOPS

BF16 (Brain Float)

No No

TF32 (TensorFloat)

No No

Compute Power

FP32 (Single Precision)

🔥 +2,078% 66.91 TFLOPS
3.072 TFLOPS

FP64 (Double Precision)

🔥 +4,255% 33.45 TFLOPS
0.768 TFLOPS

CUDA Cores

🔥 +2,100% 16,896
768

RT Cores

No 6

Architecture & Compatibility

GPU Architecture

Hopper Xe-HPG

SM (Streaming Multiprocessor)

🔥 132
No

PCIe Version

PCIe 5.0 x16 PCIe 4.0 x8

ML Software Support

CUDA Version

9.0 No

Clocks & Performance

Base Clock

🔥 1,590
2,000

Boost Clock

🔥 1,980
2,000

Memory Clock

🔥 1,313
1,937

Power Consumption

TDP/TGP

700 W
🔥 -89% 75 W

Recommended PSU

1100 W
🔥 -77% 250 W

Power Connector

None None

Rendering

Texture Units (TMU)

🔥 +1,550% 528
32

ROP

No 6

L2 Cache

🔥 +1,150% 50 MB
4 MB

Benchmarks

MLPerf, mixtral-8x7b (fp8)

6 362 tokens/s

Additional

Slots

🔥 SXM Module
Single-slot

Release Date

Oct. 17, 2022 Nov. 18, 2024

Display Outputs

No outputs
4x mini-DisplayPort 2.0
4x HDMI 2.1

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