NVIDIA H100 SXM5 96 GB vs NVIDIA Tesla X2070

Comparison of NVIDIA H100 SXM5 96 GB with 96 GB HBM3 and 16,896 cores vs NVIDIA Tesla X2070 with 6 GB GDDR5 and 448 cores.

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Performance Rating

H200 H200
MI325X MI325X
A100 A100

NVIDIA H100 SXM5 96 GB

57.9

NVIDIA H100 SXM5 96 GB

57.9
RX 7900 XTX RX 7900 XTX
MI250 MI250
Instinct MI300X Instinct MI300X

NVIDIA Tesla X2070

NVIDIA Tesla X2070

Contents:

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

Memory

Memory Size

🔥 +1,500% 96 ГБ
6 GB

Memory Type

HBM3 GDDR5

Memory Bandwidth

🔥 3.36 TB/s
177.4 GB/s

Memory Bus Width

5,120 бит 384 бит

ML Performance

FP16 (Half Precision)

🔥 267.6 TFLOPS
No

BF16 (Brain Float)

No No

TF32 (TensorFloat)

No No

Compute Power

FP32 (Single Precision)

🔥 +5,640% 66.91 TFLOPS
1.1657 TFLOPS

FP64 (Double Precision)

🔥 +5,640% 33.45 TFLOPS
0.5828 TFLOPS

CUDA Cores

🔥 +3,671% 16,896
448

RT Cores

No No

Architecture & Compatibility

GPU Architecture

Hopper Fermi

SM (Streaming Multiprocessor)

🔥 +843% 132
14

PCIe Version

PCIe 5.0 x16 MXM-B (3.0)

ML Software Support

CUDA Version

🔥 9.0
2.0

Clocks & Performance

Base Clock

🔥 1,350
No

Boost Clock

🔥 1,980
No

Memory Clock

🔥 +42% 1,313
924

Power Consumption

TDP/TGP

700 W
🔥 -68% 225 W

Recommended PSU

1100 W
🔥 -50% 550 W

Power Connector

8-pin EPS None

Rendering

Texture Units (TMU)

🔥 +843% 528
56

ROP

No No

L2 Cache

🔥 50 MB
768 KB

Benchmarks

llama.cpp, llama 7B Q4_0

🔥 +1,643% 248.8 tokens/s
14.3 tokens/s

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

🔥 +1,867% 280.7 tokens/s
14.3 tokens/s

Additional

Slots

🔥 SXM Module
MXM Module

Release Date

March 21, 2023 July 25, 2011

Display Outputs

No outputs
No outputs

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