AudD vs ACRCloud: which music recognition API fits your project?

Choosing a music recognition API shapes a lot downstream — how you authenticate, how you structure requests, and how much code you maintain. This page compares AudD and ACRCloud: both are cloud audio-fingerprinting services that take audio and return the recognized track, but they approach the problem differently. This comparison sticks to what’s verifiable and leaves the rest to your own testing.

A note on scope: the most reliable comparison is the one you run yourself. ACRCloud’s exact database size, latency, and pricing change over time and vary by plan and region, so this page focuses on AudD’s documented behavior and the structural differences between the two — not on benchmark numbers we can’t stand behind. Sign up for both and test against your real audio.

Database and recognition

AudD recognizes against a database of 160 million songs using neural-network audio fingerprinting, covering mainstream releases alongside independent and international music. Recognition holds up across audio qualities — from high-bitrate studio recordings to compressed radio streams — and tolerates background noise and artifacts, though heavily degraded sources are always harder.

ACRCloud is also an audio-fingerprinting service and additionally markets recognition for content types beyond recorded music, such as broadcast and custom audio. If your requirements extend past music recognition into other audio categories, that breadth is worth evaluating directly against ACRCloud’s current documentation.

For mainstream music, both services perform well. Differences tend to show up at the edges — specific catalogs, regions, and audio conditions — which is exactly where a test against your own inputs is more informative than any published figure.

Authentication

This is the clearest structural difference and usually the biggest code change when moving between them.

ACRCloud signs each request with an HMAC over an access key and secret, plus a timestamp. AudD authenticates with a single api_token form field — no signing string, no timestamp, no HMAC. The official SDK sets it for you from the constructor or the AUDD_API_TOKEN environment variable:

from audd import AudD

audd = AudD("your-api-token")  # or reads AUDD_API_TOKEN from the environment

song = audd.recognize("https://audd.tech/example.mp3")
if song:
    print(f"{song.artist} — {song.title}")
else:
    print("no match")  # result: null is a successful no-match, not an error

Less code on your side. The trade-off: because there’s no per-request signature, the token is a bearer-style secret — keep it server-side and rotate it from dashboard.audd.io. If you’re migrating from ACRCloud specifically, see the step-by-step migration guide.

Endpoints and API design

AudD splits recognition into three surfaces by input shape:

Standard endpoint (POST https://api.audd.io/) — a short audio clip (it analyzes up to about 12 seconds of audio), 10 MB upload cap, the single best match.
Enterprise endpoint (POST https://enterprise.audd.io/) — long audio and video, chunked server-side, billed per 12 seconds of audio, returning one match per recognized segment (a full tracklist).
Streams (addStream plus callbacks or longpoll) — continuous live audio: radio, Twitch, YouTube live.

ACRCloud separates its products by use case (identify, file scanning, broadcast monitoring) and historically by region host. Both models are reasonable; AudD’s is “pick a surface by whether your input is a clip, a file, or a live source,” with no per-region host to select. For a deeper treatment of AudD’s three surfaces, see standard, enterprise, or streams.

On AudD, a single recognition call returns structured metadata you read off the result object:

song = audd.recognize(
    "https://audd.tech/example.mp3",
    return_metadata=["apple_music", "spotify"],
)

if song:
    print(song.artist, "—", song.title)
    print("Apple Music:", song.streaming_url("apple_music"))
    print("Universal link:", song.song_link)

Metadata

AudD returns artist, title, album, release_date, label, timecode, and song_link on every standard-endpoint match. isrc and upc are returned for accounts on a Startup plan or higher. Provider blocks — apple_music, spotify, deezer, and musicbrainz — are returned only when you request them via return_metadata, so you pay latency only for the providers you render. The song_link is a universal lis.tn URL that always appears on a match and redirects the user to the song on a service they have.

If you need both music and non-music audio identification, evaluate ACRCloud’s multi-content options against your requirements. For music-focused recognition with streaming links and rights identifiers, AudD’s metadata covers the common cases directly.

SDK coverage

AudD ships 11 official SDKs — Python, Node/TypeScript, Go, Rust, PHP, Swift, Kotlin, .NET, Java, C, and C++ — so the same auth and recognition contract is available across languages without hand-rolling a client. If your stack includes a less-common language, check both providers’ SDK lists against the languages your team actually uses.

Pricing

AudD’s per-request pricing is public: 300 free requests on signup with no card, then $5 per 1,000 requests pay-as-you-go, with volume plans listed on the dashboard. The enterprise endpoint bills per 12 seconds of audio processed rather than per request, so budget around audio duration for long files and always set limit while developing.

ACRCloud publishes its own tiered pricing; because it changes and varies by plan and region, check their current pricing page directly rather than relying on a snapshot here.

Use-case fit

Radio and broadcast monitoring. AudD’s streams surface is built for continuous, real-time recognition of live audio with timestamped results — the basis for airplay monitoring and broadcast compliance. If you need to identify both music and spoken content in a single pipeline, evaluate ACRCloud’s multi-content support.

Mobile apps. AudD’s lightweight, single-call API and direct Apple Music/Spotify links keep user-facing “what’s this song?” features simple. The native Swift and Kotlin SDKs back the same recognition contract on device.

Content analysis and copyright. AudD’s label, artist, and rights identifiers (isrc/upc on Startup+) give you the metadata for rights-aware workflows, and the enterprise endpoint scans long uploads for every track. If your compliance work spans content types beyond music, weigh ACRCloud’s broader filtering against the added integration complexity.

Choosing

Choose AudD when you want fast integration with minimal configuration, music-focused recognition, real-time stream monitoring, public per-request pricing, and broad official SDK coverage.

Choose ACRCloud when you need recognition beyond music (speech or other audio categories), or your requirements lean on its specific multi-content and configuration features — and confirm the current specifics against their docs.

For most teams, both handle mainstream music well, so the decision comes down to authentication model, endpoint fit, SDK coverage for your language, and a test against your actual audio. AudD’s free tier — 300 requests, no card — makes that test cheap to run.

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