![]() Please contact for any feedback or information. The benchmark is compatible with both TensorFlow 1.x and 2.x versions. GPU with at least 2GB of RAM is required for running inference tests / 4GB of RAM for training tests. Use_CPU= : if high is selected, the benchmark will execute 10 times more runs for each test. To run inference or training only, use n_inference() or n_training().ĪIBenchmark ( use_CPU =None, verbose_level = 1 ): GPU Benchmark: System Test Download and Install for your computer - on Windows PC 10, Windows 8 or Windows 7 and Macintosh macOS 10 X, Mac 11 and above. 3DMark will recommend the best benchmark for your hardware. ![]() It has dedicated tests for all types of PC from lightweight laptops to dedicated desktops. ![]() Its a quick OpenGL benchmark as well ( online scores ). 3DMark includes everything gamers need to benchmark and compare PC performance. GPU Stress Test and OpenGL Benchmark FurMark is a lightweight but very intensive graphics card / GPU stress test on Windows platform. To run AI Benchmark, use the following code: from ai_benchmark import AIBenchmarkīenchmark = AIBenchmark () results = n ()Īlternatively, on Linux systems you can type ai-benchmark in the command line to start the tests. Windows 7, Server 2012, 2016, 2019, Windows 10, 11, Pentium4 CPU or better (x86 version), DirectX 9 or higher video, 2GB RAM. Welcome to 3DMark, the Gamer's Benchmark. It's a quick OpenGL benchmark as well ( online scores ). Note 2: For running the benchmark on Nvidia GPUs, NVIDIA CUDA and cuDNN libraries should be installed first. FurMark is a lightweight but very intensive graphics card / GPU stress test on Windows platform. Note 1: If Tensorflow is already installed in your system, you can skip the first command. If you want to check the performance of Nvidia graphic cards, run the following commands: pip install tensorflow-gpu On systems that do not have Nvidia GPUs, run the following commands to install AI Benchmark: pip install tensorflow The benchmark requires TensorFlow machine learning library to be present in your system. In total, AI Benchmark consists of 42 tests and 19 sections provided below:įor more information and results, please visit the project website: The benchmark is relying on TensorFlow machine learning library, and is providing a lightweight and accurate solution for assessing inference and training speed for key Deep Learning models. Benchmark your system and compare results online with ease - userbenchmark TechRacoon 2. AI Benchmark Alpha is an open source python library for evaluating AI performance of various hardware platforms, including CPUs, GPUs and TPUs.
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