npu-detect

Cross-platform NPU (Neural Processing Unit) detection for JavaScript.

Works in Node.js (server-side, shells out to OS tools) and Browsers (client-side, via the WebNN API).

Why?

You can query CPU info with os.cpus() and GPU info with navigator.gpu — but there's no equivalent for NPUs. This library fills that gap.

Install

npm install npu-detect

Quick Start

Node.js

const { detectNPU, hasNPU, npuSummary } = require('npu-detect');

// Full detection with details
const info = await detectNPU();
console.log(info);
// {
//   detected: true,
//   platform: 'darwin',
//   devices: [{ name: 'Apple Neural Engine (ANE)', cores: 16, ... }],
//   cpuHeuristic: { likely: true, vendor: 'Apple', npuName: 'Apple Neural Engine' },
//   ...
// }

// Quick boolean
const has = await hasNPU(); // true

// One-liner summary
const summary = await npuSummary(); // "NPU detected: Apple Neural Engine (ANE)"

Browser

import { detectNPU, hasNPU } from 'npu-detect/browser';

const info = await detectNPU({ benchmark: true });
console.log(info);
// {
//   webnnSupported: true,
//   npuAvailable: true,
//   devices: {
//     npu: { available: true, benchmark: { functional: true, execLatencyMs: 0.4 } },
//     cpu: { available: true, ... },
//     gpu: { available: true, ... },
//   },
//   ...
// }

CLI

npx npu-detect
npx npu-detect --verbose
npx npu-detect --json

How It Works

Node.js Detection (per platform)

| Platform | Method | |----------|--------| | Linux | Checks /dev/accel/* devices, lspci for NPU-class hardware, lsmod for intel_vpu/amdxdna kernel modules, sysfs for NPU frequency | | Windows | Queries Device Manager's "Neural processors" class via PowerShell (Get-PnpDevice), falls back to WMI | | macOS | Uses ioreg to find AppleNeuralEngine, infers ANE core count and TOPS from chip model, reads powermetrics for ANE power (requires root) | | All | CPU model string heuristic to identify known NPU-equipped processors (Intel Core Ultra, Snapdragon X, Ryzen AI, Apple M-series, etc.) |

Browser Detection

Uses the W3C Web Neural Network API (navigator.ml):

1. Checks if navigator.ml exists
2. Attempts navigator.ml.createContext({ deviceType: 'npu' }) — success means NPU is available
3. Optionally runs a minimal add-two-matrices computation graph to verify the device is functional
4. Also probes cpu and gpu device types for comparison

Note: WebNN requires Chrome/Edge with the flag chrome://flags/#web-machine-learning-neural-network enabled, or Edge with --disable_webnn_for_npu=0 for NPU specifically.

Supported NPU Hardware

| Vendor | NPU | Detection | |--------|-----|-----------| | Intel | AI Boost (Core Ultra / Meteor Lake, Arrow Lake, Lunar Lake) | Linux: intel_vpu module + /dev/accel/accel0. Windows: Device Manager. | | AMD | XDNA / XDNA2 (Ryzen AI, Hawk Point, Strix Point) | Linux: amdxdna module. Windows: Device Manager. | | Qualcomm | Hexagon (Snapdragon X Elite/Plus) | Windows: Device Manager. Browser: WebNN. | | Apple | Neural Engine (M1–M4, A11–A19) | macOS: ioreg + chip identification. |

API Reference

Node.js (npu-detect)

detectNPU(options?): Promise<NPUDetectionResult>

Full detection. Options:

• cpuHeuristic (boolean, default true) — also check CPU model string
• verbose (boolean, default false) — include raw OS command output

hasNPU(): Promise<boolean>

Quick boolean — confirmed NPU present?

npuSummary(): Promise<string>

Human-readable one-liner.

Browser (npu-detect/browser)

detectNPU(options?): Promise<BrowserNPUDetectionResult>

Full browser detection. Options:

• benchmark (boolean, default false) — run a test computation on each device
• probeAll (boolean, default true) — also probe CPU and GPU

hasNPU(): Promise<boolean>

Quick boolean — NPU available via WebNN?

probeDevice(deviceType): Promise<{available, error?, context?}>

Low-level probe for a specific WebNN device type.

benchmarkDevice(deviceType): Promise<{functional, buildLatencyMs?, execLatencyMs?, error?}>

Run a minimal computation on a device and measure latency.

Caveats

• Linux: NPU detection requires the kernel module to be loaded and /dev/accel/ to be populated. Some sysfs paths require root.
• Windows: PowerShell queries may be slow (~1-2s). The "NeuralProcessor" PnP class requires up-to-date drivers.
• macOS: Apple provides almost no public API for ANE introspection. Detection relies on ioreg and chip identification. powermetrics requires sudo.
• Browser: WebNN is still an emerging standard. NPU support requires specific browser flags and up-to-date GPU/NPU drivers.
• CPU Heuristic: The CPU model string check is a "best guess" — it tells you the CPU should have an NPU, not that it's accessible.

License

MIT