NVIDIA Tesla M40 24 GB vs NVIDIA Jetson AGX Orin 32 GB

VS

NVIDIA Tesla M40 24 GB

NVIDIA Jetson AGX Orin 32 GB

We compared two Professional market GPUs: 24GB VRAM Tesla M40 24 GB and 32GB VRAM Jetson AGX Orin 32 GB to see which GPU has better performance in key specifications, benchmark tests, power consumption, etc.

Main Differences

NVIDIA Tesla M40 24 GB 's Advantages

Boost Clock1112MHz

Larger VRAM bandwidth (288.4GB/s vs 204.8GB/s)

1280 additional rendering cores

NVIDIA Jetson AGX Orin 32 GB 's Advantages

Released 7 years and 3 months late

More VRAM (32GB vs 24GB)

Lower TDP (40W vs 250W)

Score

Benchmark

FP32 (float)

Tesla M40 24 GB +104%

6.832 TFLOPS

Jetson AGX Orin 32 GB

3.333 TFLOPS

Tesla M40 24 GB

VS

Jetson AGX Orin 32 GB

Graphics Card

Nov 2015

Release Date

Feb 2023

Tesla Maxwell

Generation

Tegra

Professional

Type

Professional

PCIe 3.0 x16

Bus Interface

PCIe 4.0 x4

Clock Speeds

948 MHz

Base Clock

-

1112 MHz

Boost Clock

-

1502 MHz

Memory Clock

1600 MHz

Memory

24GB

Memory Size

32GB

GDDR5

Memory Type

LPDDR5

384bit

Memory Bus

256bit

288.4GB/s

Bandwidth

204.8GB/s

Render Config

-

SM Count

14

3072

Shading Units

1792

192

TMUs

56

96

ROPs

24

-

Tensor Cores

56

-

48 KB (per SMM)

L1 Cache

128 KB (per SM)

3 MB

L2 Cache

256 KB

-

Theoretical Performance

106.8 GPixel/s

Pixel Rate

22.32 GPixel/s

213.5 GTexel/s

Texture Rate

52.08 GTexel/s

-

FP16 (half)

6.666 TFLOPS

6.832 TFLOPS

FP32 (float)

3.333 TFLOPS

213.5 GFLOPS

FP64 (double)

1.667 TFLOPS

Board Design

250W

TDP

40W

600 W

Suggested PSU

-

No outputs

Outputs

Portable Device Dependent

8-pin EPS

Power Connectors

-

Graphics Processor

GM200

GPU Name

GA10B

GM200-895-A1

GPU Variant

-

Maxwell 2.0

Architecture

Ampere

TSMC

Foundry

Samsung

28 nm

Process Size

8 nm

8 billion

Transistors

Unknown

601 mm²

Die Size

Unknown

Graphics Features

12 (12_1)

DirectX

12 Ultimate (12_2)

4.6

OpenGL

4.6

3.0

OpenCL

3.0

1.3

Vulkan

1.3

5.2

CUDA

8.6

6.7

Shader Model

6.7

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