Classifies GPUs based on their 3D rendering benchmark score allowing the developer to provide sensible default settings for graphically intensive applications. Think of it like a user-agent detection for the GPU but more powerful.
By default we use the UNPKG CDN to host the benchmark data. If you would like to serve the benchmark data yourself download the required benchmarking data from benchmarks.tar.gz and serve it from a public directory.
Make sure you have Node.js installed.
$ npm install detect-gpu
import { getGPUTier } from 'detect-gpu';
(async () => {
const gpuTier = await getGPUTier({
benchmarksURL?: string; // (Default, "https://unpkg.com/detect-gpu@${PKG_VERSION}/dist/benchmarks") Provide location of where to access benchmark data
failIfMajorPerformanceCaveat?: boolean; // (Default, false) Fail to detect if the WebGL implementation determines the performance would be dramatically lower than the equivalent OpenGL
glContext?: WebGLRenderingContext | WebGL2RenderingContext; // (Default, undefined) Optionally pass in a WebGL context to avoid creating a temporary one internally
desktopTiers?: number[]; // (Default, [0, 15, 30, 60]) Framerate per tier
mobileTiers?: number[]; // (Default, [0, 15, 30, 60]) Framerate per tier
override?: { // (Default, false) Override specific functionality, useful for development
renderer?: string; // Manually override reported GPU renderer string
isIpad?: boolean; // Manually report device as being an iPad
isMobile?: boolean; // Manually report device as being a mobile device
screenSize?: { width: number; height: number }; // Manually adjust reported screenSize
loadBenchmarks?: (file: string) => Promise<TModelEntry[] | undefined>; // Optionally modify method for loading benchmark data
};
})
// Example output:
// {
// "tier": 1,
// "isMobile": false,
// "type": "BENCHMARK",
// "fps": 21,
// "gpu": "intel iris graphics 6100"
// }
})();
detect-gpu
uses rendering benchmark scores (framerate, normalized by resolution) in order to determine what tier should be assigned to the user's GPU. If no WebGLContext
can be created, the GPU is blocklisted or the GPU has reported to render on less than 15 fps
tier: 0
is assigned. One should provide a fallback to a non-WebGL experience.
Based on the reported fps
the GPU is then classified into either tier: 1 (>= 15 fps)
, tier: 2 (>= 30 fps)
or tier: 3 (>= 60 fps)
. The higher the tier the more graphically intensive workload you can offer to the user.
Special care has been taken to make sure all browsers that support WebGL
are also supported by detect-gpu
including IE 11
.
My work is released under the MIT license.
detect-gpu
uses both mobile and desktop benchmarking scores from https://gfxbench.com.