NVIDIA H200 SXM 141 GB vs WOLF RTX 5000E DUAL VO 6U VPX (WOLF 2538)

Comparison of NVIDIA H200 SXM 141 GB with 141 GB HBM3e and 16,896 cores vs WOLF RTX 5000E DUAL VO 6U VPX (WOLF 2538) with 16 GB GDDR6 and 9,728 cores.

Loading...

Performance Rating

NVIDIA H200 SXM 141 GB outperforms WOLF RTX 5000E DUAL VO 6U VPX (WOLF 2538) by 333.31% in the overall GPU ARK performance rating

A100 A100
H200 H200
MI325X MI325X

NVIDIA H200 SXM 141 GB

67.4

NVIDIA H200 SXM 141 GB

67.4
RX 7900 XTX RX 7900 XTX
MI250 MI250
Instinct MI300X Instinct MI300X

WOLF RTX 5000E DUAL VO 6U VPX (WOLF 2538)

15.6

WOLF RTX 5000E DUAL VO 6U VPX (WOLF 2538)

15.6

Contents:

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

Memory

Memory Size

🔥 +781% 141 ГБ
16 ГБ ×2 (32 ГБ)

Memory Type

HBM3e GDDR6

Memory Bandwidth

🔥 4.89 TB/s
576.0 GB/s ×2 (1152 GB/s)

Memory Bus Width

6,144 бит 256 бит ×2 (512 бит)

ML Performance

FP16 (Half Precision)

🔥 +719% 267.6 TFLOPS
32.69 TFLOPS

BF16 (Brain Float)

No No

TF32 (TensorFloat)

No No

Compute Power

FP32 (Single Precision)

🔥 +105% 66.91 TFLOPS
32.69 TFLOPS

FP64 (Double Precision)

33.45 TFLOPS
🔥 +1,526,656% 510,700.0 TFLOPS

CUDA Cores

🔥 +74% 16,896
9,728 ×2 (19456)

RT Cores

No
🔥 76 ×2 (152)

Architecture & Compatibility

GPU Architecture

Hopper Ada Lovelace

SM (Streaming Multiprocessor)

🔥 +74% 132
76

PCIe Version

PCIe 5.0 x16 PCIe 4.0 x16

ML Software Support

CUDA Version

🔥 9.0
8.9

Clocks & Performance

Base Clock

🔥 +61% 1,500
930

Boost Clock

🔥 +18% 1,980
1,680

Memory Clock

1,593
🔥 +41% 2,250

Power Consumption

TDP/TGP

700 W
🔥 -79% 150 W

Recommended PSU

1100 W No

Power Connector

8-pin EPS None

Rendering

Texture Units (TMU)

🔥 +74% 528
304 ×2 (608)

ROP

No
🔥 76 ×2 (152)

L2 Cache

50 MB
🔥 +28% 64 MB

Benchmarks

MLPerf, llama2-70b-99.9 (UNSET)

3 534 tokens/s

MLPerf, llama2-70b-99.9 (fp16)

3 553 tokens/s

MLPerf, llama2-70b-99.9 (fp8)

2 444 tokens/s

MLPerf, llama3.1-405b (fp16)

40.8 tokens/s

MLPerf, llama3.1-405b (fp8)

25.3 tokens/s

MLPerf, llama3.1-8b (fp8)

5 161 tokens/s

MLPerf, deepseek-r1 (fp8)

1 113 tokens/s

MLPerf, mixtral-8x7b (fp8)

7 132 tokens/s

Additional

Slots

🔥 SXM Module
IGP

Release Date

Nov. 18, 2024 March 21, 2023

Display Outputs

No outputs
Portable Device Dependent

Renting is cheaper than buying