NVIDIA H200 SXM 141 GB vs NVIDIA Riva TNT2 M64 Vanta-16

Comparison of NVIDIA H200 SXM 141 GB with 141 GB HBM3e and 16,896 cores vs NVIDIA Riva TNT2 M64 Vanta-16 with 16 GB SDR.

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Performance Rating

H200 H200
MI325X MI325X
A100 A100

NVIDIA H200 SXM 141 GB

NVIDIA H200 SXM 141 GB

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

NVIDIA Riva TNT2 M64 Vanta-16

NVIDIA Riva TNT2 M64 Vanta-16

Contents:

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

Memory

Memory Size

141 GB 16 MB

Memory Type

HBM3e SDR

Memory Bandwidth

4.89 TB/s 1.064 GB/s

Memory Bus Width

6,144 бит 64 бит

ML Performance

FP16 (Half Precision)

267.6 TFLOPS No

BF16 (Brain Float)

No No

TF32 (TensorFloat)

No No

Compute Power

FP32 (Single Precision)

66.91 TFLOPS No

FP64 (Double Precision)

33.45 TFLOPS No

CUDA Cores

16,896 No

RT Cores

No No

Architecture & Compatibility

GPU Architecture

Hopper Fahrenheit

SM (Streaming Multiprocessor)

132 No

PCIe Version

PCIe 5.0 x16 AGP 4x

ML Software Support

CUDA Version

9.0 No

Clocks & Performance

Base Clock

1,500 No

Boost Clock

1,980 No

Memory Clock

1,593 133

Power Consumption

TDP/TGP

700 W unknown

Recommended PSU

1100 W
🔥 -82% 200 W

Power Connector

8-pin EPS None

Rendering

Texture Units (TMU)

528 2

ROP

No No

L2 Cache

50 MB No

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 Single-slot

Release Date

Nov. 18, 2024 March 22, 1999

Display Outputs

No outputs
1x VGA

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