AMD Radeon Instinct MI325X vs Xiaomi GeForce MX150

Comparison AMD Radeon Instinct MI325X with 288 GB HBM3e and 19,456 cores vs Xiaomi GeForce MX150 with 2 GB GDDR5 and 384 cores.

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Performance Rating

AMD Radeon Instinct MI325X outperforms Xiaomi GeForce MX150 by 11,394.25% in the overall GPU ARK performance rating

A100 A100
H200 H200
MI325X MI325X

AMD Radeon Instinct MI325X

100.0

AMD Radeon Instinct MI325X

100.0
RX 7900 XTX RX 7900 XTX
MI250 MI250
Instinct MI300X Instinct MI300X

Xiaomi GeForce MX150

0.9

Xiaomi GeForce MX150

0.9

Expert Comparison

AMD Radeon Instinct MI325X значительно превосходит Xiaomi GeForce MX150 по всем параметрам. MI325X имеет гораздо больше ядер, большую память и пропускную способность, а также более высокую производительность в FP32. MI325X предназначена для мощных вычислений, в то время как MX150 подходит для легких задач, таких как офисная работа или базовые игры.

Contents:

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

Memory

Memory Size

🔥 +14,300% 288 ГБ
2 GB

Memory Type

HBM3e GDDR5

Memory Bandwidth

🔥 10.3 TB/s
40.10 GB/s

Memory Bus Width

8,192 бит 64 бит

ML Performance

FP16 (Half Precision)

🔥 +4,060,148% 653.7 TFLOPS
0.0161 TFLOPS

BF16 (Brain Float)

No No

TF32 (TensorFloat)

No No

Compute Power

FP32 (Single Precision)

🔥 +7,835% 81.72 TFLOPS
1.0299 TFLOPS

FP64 (Double Precision)

🔥 +253,689% 81.72 TFLOPS
0.0322 TFLOPS

CUDA Cores

🔥 +4,967% 19,456
384

RT Cores

No No

Architecture & Compatibility

GPU Architecture

CDNA 3.0 Pascal

SM (Streaming Multiprocessor)

No 3

PCIe Version

PCIe 5.0 x16 PCIe 3.0 x4

ML Software Support

CUDA Version

No 6.1

CUDA Toolkit (first supported)

v8

CUDA Toolkit (deprecated)

v12

CUDA Toolkit (support removed)

v13

CUDA Toolkit status

Supported Removed

Clocks & Performance

Base Clock

🔥 1,000
1,252

Boost Clock

🔥 +57% 2,100
1,341

Memory Clock

🔥 +102% 2,525
1,253

Power Consumption

Recommended PSU

1400 W No

Power Connector

None None

TDP/TGP

1000 W
🔥 -99% 10 W

Rendering

Texture Units (TMU)

🔥 +4,967% 1,216
24

ROP

No No

L2 Cache

🔥 16 MB
512 KB

Benchmarks

MLPerf, llama2-70b-99.9 (Dummy)

3 596 tokens/s

MLPerf, llama2-70b-99.9 (fp8)

1 946 tokens/s

llama.cpp, llama-2-7b-Q4_0

22.4 tokens/s

MLPerf, mixtral-8x7b (fp8)

6 975 tokens/s

Additional

Slots

OAM Module IGP

Release Date

Oct. 12, 2024 May 17, 2017

Display Outputs

No outputs
Portable Device Dependent

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