Guide
LUFS Checker and Online Loudness Meter for Music
Marc Aaron Jacobs
Founder, DropCue · Composer
LUFS is the unit streaming platforms actually listen to, not the peak meter on your DAW. DropCue reads integrated LUFS (to the ITU-R BS.1770 standard) on any track in your library and, when you want it, masters that track to streaming-ready loudness in seconds.
Who this is for
You searched "LUFS checker" or "loudness meter online" because something does not add up. Your mix sounds loud in the studio, then gets quiet on Spotify. Or a client asked you to "hit -14 LUFS" and you are not totally sure what that means, where to read it, or whether your bounce is even close. You are a composer, a producer, a mixer, or a sync writer who needs to know one number on a finished track and does not want to install a plugin, open a session, and re-render just to find it.
Here is the honest version. LUFS (Loudness Units relative to Full Scale) measures perceived loudness over time, not the instantaneous peak your DAW shows you. A track can peak at 0 dBFS and still measure quiet, because LUFS accounts for how loud the whole thing actually feels across its duration. That is the number streaming services normalize against. So if you are reading peak meters and wondering why your "loud" master gets turned down, you are reading the wrong meter. If the term itself is new, what is LUFS breaks down the full definition.
This page is for the working musician who wants the right meter, attached to the tracks they already have, with a plain-language read on whether the loudness is in the safe zone for streaming and what to do if it is not. Not a science project. A number, a verdict, and a fix.
The audience-specific reality
Loudness for streaming is one of the most over-mythologized topics in music. The widely published reference point is that the major platforms normalize playback toward roughly -14 LUFS integrated (Spotify and YouTube sit around there; Apple Music references a slightly different internal target). The exact figures shift over time and platforms rarely confirm them down to the decimal, so anyone quoting you an exact universal number with total confidence is overselling. The useful takeaway is the shape of it: master much louder than the normalization target and the platform turns you down (and you can lose dynamics and pick up distortion for nothing); master much quieter and you may get turned up, or just sit weak next to everything else in a playlist.
What makes the LUFS question different from "does my mix sound good" is that it is measurable and standardized. The measurement method is defined by ITU-R BS.1770, the international recommendation for loudness metering. That is why a credible LUFS reading is not a vibe; it is integrated loudness computed the same way professional broadcast and streaming systems compute it. When a tool says it reads "integrated LUFS to ITU-R BS.1770," that is the difference between a real meter and a guess.
One honest caveat that most online "LUFS checkers" will not tell you: if you measure a lossy file (MP3, AAC, a compressed export) instead of the original WAV or FLAC, the loudness and especially the true peak readings can be slightly skewed versus the source. The codec changes the waveform. A good tool flags that as approximate rather than pretending the number is gospel. We do.
Why DropCue fits this workflow
Most LUFS checkers are a single-purpose web upload box. You drag a file in, get a number, close the tab, and you are no closer to fixing anything. DropCue is the opposite end of that: your catalog already lives here, so the loudness read happens on the tracks you are actually pitching, sharing, and licensing, not on a one-off file you uploaded just to satisfy curiosity.
AI Mix Analysis (powered by ROEX) is the meter. Point it at any track in your library and it returns integrated LUFS measured to ITU-R BS.1770, plus true peak, clipping detection, stereo width, mono compatibility, phase, and tonal balance. Then, because raw numbers are not the same as knowing what to do, it adds plain-language recommendations: what is off and how to address it. That is the part a bare loudness meter never gives you. And for lossy or compressed sources it tells you when the loudness and peak figures are approximate rather than dressing up a soft number as precise.
AI Mastering (powered by Chosen Masters) is the fix. Once you know a track is sitting too quiet or peaking into distortion, pick a style (Modern, Open, or Powerful) and get a master that lands at streaming-ready loudness in seconds. You can A/B the before and after loudness-matched, with a moving waveform and studio analytics (the same integrated LUFS to ITU-R BS.1770, true peak and inter-sample peaks, dynamics, L/R correlation, EQ) so you are judging the music, not just the volume jump.
The point is the loop closes in one place. Check loudness, understand it, master to target, re-check, share or license. No bouncing between your DAW, a standalone loudness meter, a spectrum analyzer, and a separate mastering service, each with its own upload and its own tab. Your catalog, the meter, and the mastering engine are the same product.
The features that matter most
✓ AI Mix Analysis (ROEX): integrated LUFS to ITU-R BS.1770
This is your loudness meter. It reads integrated LUFS the standardized way, the same metric streaming platforms normalize against, so the number you see is the number that matters for playback.
✓ True peak and clipping detection
LUFS tells you perceived loudness; true peak (including inter-sample peaks) tells you whether you are clipping on conversion. Reading both is how you avoid distortion that a simple peak meter misses.
✓ Plain-language recommendations
A bare meter gives you -19 LUFS and silence. ROEX tells you that is sitting quiet for streaming and what to do about it, so you are not left translating numbers into action on your own.
✓ AI Mastering (Chosen Masters) to streaming-ready loudness
Once you know a track is under or over target, pick a style and master it to a competitive, streaming-ready level in seconds instead of guessing at a limiter setting and re-rendering.
✓ Loudness-matched A/B with moving waveform and analytics
Comparing masters at matched loudness is the only honest A/B. Louder always sounds better at first; matching levels lets you hear whether the master is actually improved, with LUFS, true peak, dynamics, and correlation shown.
✓ Lossy-source approximation flagging
If you measure an MP3 instead of the WAV, the readings can be skewed. DropCue flags those figures as approximate rather than pretending compressed-file loudness is exact, so you trust the number for the right reasons.
Names you may know in this space
ITU-R BS.1770
The international recommendation that defines how integrated loudness (LUFS) is measured. It is the standard DropCue's analysis reads against, which is what makes the number a real meter rather than an estimate.
Spotify
Normalizes playback loudness toward a published reference around -14 LUFS integrated, which is why mastering much louder than that often just gets your track turned down.
YouTube
Also normalizes loud uploads downward toward a similar zone, so a brick-walled master gains you distortion and lost dynamics without gaining playback volume.
Apple Music
Uses its own internal loudness reference (Sound Check) rather than the exact same target, a reminder that there is no single universal number, only a safe range.
Pricing for this audience
Pro plans include 10 free Mix Analysis runs and 10 free AI Masters to start; after that, analysis packs are 20 for $4.99 or 50 for $9.99 (never expire), and mastering packs run 10 for $9.99, 25 for $21.99, or 50 for $39.99 (never expire), or 15 masters a month for $12. Starter plans can buy the same packs. DropCue itself starts at $5/mo for Starter (annual, 500 tracks) and $15/mo for Pro (annual, 1,000 tracks). No add-ons, no per-track fees, no revenue share, and you keep 100% of your placement fees.
Frequently asked questions
What LUFS should I master my music to for streaming?
There is no single magic number, but the widely published reference is that Spotify and YouTube normalize toward roughly -14 LUFS integrated, and Apple Music uses its own internal target. The practical goal is to land in that safe range rather than master much louder (which gets turned down) or much quieter (which sits weak in playlists). DropCue's AI Mastering targets streaming-ready loudness so you do not have to guess.
How is this different from a free online LUFS meter?
A free online meter is a one-off upload box: drag a file in, get a number, close the tab. DropCue reads integrated LUFS (to ITU-R BS.1770) directly on the tracks already in your catalog, adds true peak, clipping, stereo, and tonal data, explains what to fix in plain language, and lets you actually master the track to target without leaving the app.
Is the LUFS reading accurate?
It is measured to ITU-R BS.1770, the international standard streaming platforms use, so for WAV or FLAC sources it is a real, standardized reading. For lossy files (MP3, AAC) the loudness and especially true peak figures can be slightly skewed by the codec versus the original, and DropCue flags those as approximate rather than presenting them as exact. Measure the highest-quality file you have for the truest number.
What is the difference between LUFS and peak level?
Peak level is the loudest instantaneous sample (or inter-sample peak), and it is what a normal DAW meter shows. LUFS measures perceived loudness over the whole track, accounting for how loud it actually feels across time. Streaming platforms normalize against LUFS, not peak, which is why a track can peak at 0 dBFS and still get turned up or down. DropCue's Mix Analysis reads both so you see the full picture.
Can DropCue fix a track that measures too quiet or too loud?
Yes. After Mix Analysis tells you where the loudness sits, AI Mastering (powered by Chosen Masters) masters the track to streaming-ready loudness in seconds. You pick a style (Modern, Open, or Powerful) and A/B the before and after loudness-matched, with a moving waveform and studio analytics including integrated LUFS, true peak, dynamics, and L/R correlation.
Do I need to upload files just to check loudness?
No. The whole point is that your catalog already lives in DropCue, so Mix Analysis runs on tracks you have already uploaded for pitching, sharing, and licensing. You are not maintaining a separate file somewhere just to satisfy a loudness meter; the meter, the catalog, and the mastering engine are the same product.
