Migrating from
detect-gpu? This package has moved to@pmndrs/detect-gpu. Update your imports:- import { getGPUTier } from 'detect-gpu'; + import { getGPUTier } from '@pmndrs/detect-gpu';
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.
Note: Our benchmark data source (gfxbench.com) stopped updating in December 2025. The current data remains accurate for existing GPUs, but we are exploring alternative data sources for future updates. See #132 for progress.
pnpm add @pmndrs/detect-gpunpm install @pmndrs/detect-gpuyarn add @pmndrs/detect-gpuBy default benchmark data is loaded from the UNPKG CDN (https://unpkg.com/@pmndrs/detect-gpu@{version}/dist/benchmarks). To serve it yourself (e.g. for offline environments, strict CSP, or to avoid a third-party CDN):
- Download benchmarks.tar.gz and extract it into a publicly served directory — for example
public/benchmarks/in your app. - Point
getGPUTierat that URL via thebenchmarksURLoption:
const gpuTier = await getGPUTier({
benchmarksURL: '/benchmarks',
});The directory must be served at the exact URL passed in — detect-gpu appends filenames like /benchmarks-d-*.json to it when fetching.
import { getGPUTier } from '@pmndrs/detect-gpu';
const gpuTier = await getGPUTier();
// 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.
getGPUTier() returns a type field indicating how the result was produced:
type |
Meaning |
|---|---|
BENCHMARK |
Matched a benchmark entry; fps reflects the measured framerate for that GPU. |
FALLBACK |
Renderer recognised but no benchmark match found. tier is a conservative default. |
BENCHMARK_FETCH_FAILED |
Benchmark fetch failed (CDN outage, strict CSP, offline, etc.). Safe to retry. |
BLOCKLISTED |
Renderer is on a known-bad list (drivers with severe issues). tier is always 0. |
WEBGL_UNSUPPORTED |
No WebGL context could be created. tier is always 0. |
SSR |
Running server-side — no window, detection skipped. |
The fps field is populated only for BENCHMARK results. All other type values leave fps as undefined.
getGPUTier({
/**
* URL of directory where benchmark data is hosted.
*
* @default https://unpkg.com/@pmndrs/detect-gpu@{version}/dist/benchmarks
*/
benchmarksURL?: string;
/**
* Optionally pass in a WebGL context to avoid creating a temporary one
* internally.
*/
glContext?: WebGLRenderingContext | WebGL2RenderingContext;
/**
* Whether to fail if the system performance is low or if no hardware GPU is
* available.
*
* @default false
*/
failIfMajorPerformanceCaveat?: boolean;
/**
* Framerate per tier for mobile devices.
*
* @defaultValue [0, 15, 30, 60]
*/
mobileTiers?: number[];
/**
* Framerate per tier for desktop devices.
*
* @defaultValue [0, 15, 30, 60]
*/
desktopTiers?: number[];
/**
* Optionally override specific parameters. Used mainly for testing.
*/
override?: {
renderer?: string;
/**
* Override whether device is an iPad.
*/
isIpad?: boolean;
/**
* Override whether device is a mobile device.
*/
isMobile?: boolean;
/**
* Override device screen size.
*/
screenSize?: { width: number; height: number };
/**
* Override how benchmark data is loaded
*/
loadBenchmarks?: (file: string) => Promise<ModelEntry[]>;
};
})- Node.js 24+
- ESM only (CommonJS is not supported)
All modern browsers that support WebGL are supported.
Released under the MIT license.
@pmndrs/detect-gpu uses both mobile and desktop benchmarking scores from https://gfxbench.com.