AI Benchmark is an open source python library for evaluating AI performance of various hardware platforms, including CPUs, GPUs and TPUs. The benchmark is relying on TensorFlow machine learning library, and is providing a lightweight solution for assessing inference and training speed for key Deep Learning models, including:

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1. MobileNet-V2
2. Inception-V3
3. Inception-V4
4. Inception-ResNet-V2
5. ResNet-V2-50
6. ResNet-V2-152
7. VGG-16
8. SRCNN 9-5-5
9. VGG-19
10. ResNet-SRGAN
11. ResNet-DPED
12. U-Net
13. Nvidia-SPADE
14. ICNet
15. PSPNet
16. DeepLab
17. Pixel-RNN
18. LSTM
19. GNMT

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It is currently distributed as a Python pip package, installation instructions can be found at http://ai-benchmark.com/alpha.html and https://pypi.org/project/ai-benchmark/

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Note: Fast installation [if TensorFlow is already installed]:

1. pip install ai-benchmark
2. Run benchmark using the following python code:
   1. from ai_benchmark import AIBenchmark
   2. results = AIBenchmark().run()

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A detailed information about test setups: http://ai-benchmark.com/ranking_cpus_and_gpus_detailed.html

A short preliminary ranking is available here: http://ai-benchmark.com/ranking_cpus_and_gpus.html

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A global ranking with the results of various hardware and software platforms, drivers / configs and TF builds should be available soon. Original post: http://ai-benchmark.com/alpha.html