It also means that it's not using special hardware like Nvidia's Tensor cores or Intel's XMX cores. That uses DirectCompute rather than PyTorch, which means it will run on any DirectX 11 compatible GPU - yes, including things like Intel integrated graphics.
#Benchmark test gpu nvidia at store windows
There's also this Const-Me project, WhisperDesktop, which is a Windows executable written in C++. Of course there's the OpenAI GitHub (instructions and details below). There are a few options for running Whisper, on Windows or otherwise. We wanted to let the various GPUs stretch their legs a bit and show just how fast they can go. Real-time speech recognition only needs to keep up with maybe 100–150 words per minute (maybe a bit more if someone is a fast talker). We did not attempt to use it in that fashion, as we were more interesting in checking performance. Note also that Whisper can be used in real-time to do speech recognition, similar to what you can get through Windows or Dragon NaturallySpeaking. You can also run it on your CPU, though the speed drops precipitously. The last one is our subject today, and it can provide substantially faster than real-time transcription of audio via your GPU, with the entire process running locally for free. Besides ChatGPT, Bard, and Bing Chat (aka Sydney), which all run on data center hardware, you can run your own local version of Stable Diffusion, Text Generation, and various other tools. The best graphics cards aren't just for gaming, especially not when AI-based algorithms are all the rage.
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