AMD Radeon Instinct MI300X vs NVIDIA GeForce GTX 1070 Engineering Sample

Comparison of AMD Radeon Instinct MI300X with 192 GB HBM3 and 19,456 cores vs NVIDIA GeForce GTX 1070 Engineering Sample with 8 GB GDDR5 and 1,920 cores.

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Performance Rating

H200 H200
MI325X MI325X
A100 A100

AMD Radeon Instinct MI300X

AMD Radeon Instinct MI300X

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

NVIDIA GeForce GTX 1070 Engineering Sample

NVIDIA GeForce GTX 1070 Engineering Sample

Contents:

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

Memory

Memory Size

192 GB 8 GB

Memory Type

HBM3 GDDR5

Memory Bandwidth

10.3 TB/s 256.3 GB/s

Memory Bus Width

8,192 бит 256 бит

ML Performance

FP16 (Half Precision)

653.7 TFLOPS 0.101 TFLOPS

BF16 (Brain Float)

No No

TF32 (TensorFloat)

No No

Compute Power

FP32 (Single Precision)

81.72 TFLOPS 6.463 TFLOPS

FP64 (Double Precision)

81.72 TFLOPS 0.202 TFLOPS

CUDA Cores

19,456 1,920

RT Cores

No No

Architecture & Compatibility

GPU Architecture

CDNA 3.0 Pascal

SM (Streaming Multiprocessor)

No 15

PCIe Version

PCIe 5.0 x16 PCIe 3.0 x16

ML Software Support

CUDA Version

No 6.1

Clocks & Performance

Base Clock

1,000 1,506

Boost Clock

2,100 1,683

Memory Clock

2,525 2,002

Power Consumption

TDP/TGP

750 W
🔥 -80% 150 W

Recommended PSU

1150 W
🔥 -61% 450 W

Power Connector

None 1x 8-pin

Rendering

Texture Units (TMU)

1,216 120

ROP

No No

L2 Cache

16 MB 2 MB

Benchmarks

MLPerf, llama2-70b-99.9 (UNSET)

1 983 tokens/s

MLPerf, llama2-70b-99.9 (fp16)

1 740 tokens/s

MLPerf, llama2-70b-99.9 (fp8)

1 057 tokens/s

MLPerf, llama3.1-405b (UNSET)

30.4 tokens/s

MLPerf, llama3.1-405b (fp16)

34.8 tokens/s

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

232.9 tokens/s

MLPerf, mixtral-8x7b (fp8)

5 975 tokens/s

Additional

Slots

OAM Module Dual-slot

Release Date

Dec. 6, 2023 No

Display Outputs

No outputs
1x DVI
1x HDMI 2.0
3x DisplayPort 1.4a

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