HP GT 630M 2 GB vs NVIDIA H200 SXM 141 GB

Comparison of HP GT 630M 2 GB with 2 GB GDDR5 and 96 cores vs NVIDIA H200 SXM 141 GB with 141 GB HBM3e and 16,896 cores.

Loading...

Performance Rating

H200 H200
MI325X MI325X
A100 A100

HP GT 630M 2 GB

HP GT 630M 2 GB

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

NVIDIA H200 SXM 141 GB

NVIDIA H200 SXM 141 GB

Contents:

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

Memory

Memory Size

2 GB 141 GB

Memory Type

GDDR5 HBM3e

Memory Bandwidth

57.60 GB/s 4.89 TB/s

Memory Bus Width

128 бит 6,144 бит

ML Performance

FP16 (Half Precision)

No 267.6 TFLOPS

BF16 (Brain Float)

No No

TF32 (TensorFloat)

No No

Compute Power

FP32 (Single Precision)

0.3072 TFLOPS 66.91 TFLOPS

FP64 (Double Precision)

0.0256 TFLOPS 33.45 TFLOPS

CUDA Cores

96 16,896

RT Cores

No No

Architecture & Compatibility

GPU Architecture

Fermi 2.0 Hopper

SM (Streaming Multiprocessor)

2 132

PCIe Version

MXM-A (3.0) PCIe 5.0 x16

ML Software Support

CUDA Version

2.1
🔥 9.0

Clocks & Performance

Base Clock

No 1,500

Boost Clock

No 1,980

Memory Clock

900 1,593

Power Consumption

TDP/TGP

🔥 -95% 33 W
700 W

Recommended PSU

No 1100 W

Power Connector

None 8-pin EPS

Rendering

Texture Units (TMU)

16 528

ROP

No No

L2 Cache

256 KB 50 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

MXM Module SXM Module

Release Date

March 22, 2012 Nov. 18, 2024

Display Outputs

Portable Device Dependent
No outputs

Renting is cheaper than buying