Normalize Audio Volume Free
Fix quiet, uneven, or too-loud audio files online for free. Choose between peak normalization (sets the loudest sample to 0 dBFS) and loudness normalization (LUFS — matches streaming platform targets of −14 LUFS for YouTube/Spotify or −16 LUFS for podcasts). MP3, WAV, M4A, FLAC. Batch up to 10 files. No signup, no watermark.
Drop your audio files here
MP3 · WAV · M4A · FLAC · OGG — up to 10 files
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Normalization Settings
No account required · Files deleted in 24h
Normalizing audio…
Analysing levels
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Normalization Complete!
Your normalized audio is ready.
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Pro — batch 100 files, dynamic range compression, true peak limiting, API
API access · Priority queue · Team workspace
How It Works
Upload Audio Files
Upload up to 10 MP3, WAV, M4A, FLAC, or OGG files. All files in the batch will be normalized using the same settings. Upload multiple files to normalize a whole album, podcast series, or set of sound effects to a consistent loudness level.
Choose Normalization Mode
Peak normalization measures the highest amplitude sample in the file and applies a single gain value to bring it to −0.1 dBFS (just below the maximum digital level). Loudness normalization (LUFS) measures the average perceived loudness across the whole file using the ITU-R BS.1770 algorithm and applies gain to match the target — more accurate to how human hearing perceives volume difference.
Download Normalized Audio
Download your normalized audio. A report shows the input level (peak dBFS or integrated LUFS) and the gain applied. Multiple files are packaged in a ZIP. The output format matches the input by default — or choose MP3, WAV, or M4A to convert format at the same time.
Normalize Audio Features
Peak Normalization
Peak normalization finds the maximum sample amplitude in the file and applies a linear gain to bring it to −0.1 dBFS (0.1 dB below the digital maximum, leaving a small headroom margin). This ensures the audio is as loud as possible without any clipping. All audio samples are scaled by the same gain factor — the dynamic range and tonal character of the recording are preserved exactly.
LUFS Loudness Normalization
LUFS (Loudness Units relative to Full Scale) normalization uses the ITU-R BS.1770 algorithm to measure integrated loudness — average perceptual loudness weighted to match human hearing. −14 LUFS is the target used by YouTube, Spotify, Apple Music, and most streaming platforms. −16 LUFS is recommended by Apple Podcasts. −23 LUFS is the EBU R128 broadcast standard for TV and radio.
Batch — 10 Files
Normalize up to 10 audio files in one batch to the same loudness target. Essential for podcast producers who need all episodes at −16 LUFS, music artists releasing an album where all tracks should be at consistent loudness, game developers normalizing sound effects to a standard level, and content creators preparing a video's audio tracks to match YouTube's −14 LUFS target before upload.
Level Analysis Report
After normalization, a report shows: input peak (dBFS), input integrated loudness (LUFS), gain applied (dB), and output peak. This lets you understand exactly what adjustment was made and verify the output meets your target. If the input is already louder than the target (e.g. a file at −10 LUFS being normalized to −14 LUFS), the tool applies negative gain (reduces volume) rather than clipping.
Two-Pass Processing
LUFS normalization uses a two-pass process: Pass 1 analyses the entire file to measure integrated loudness; Pass 2 applies the calculated gain. This two-pass method ensures accurate loudness measurement regardless of file length. Peak normalization is a single-pass process (find peak, apply gain). Both methods are lossless in the sense that no audio data is discarded — only the amplitude scaling changes.
Private & No Account Needed
TLS 1.3 encrypted uploads. Files deleted within 24 hours. No watermarks. No account or signup required for the free tier. Audio is never stored, shared, or used for training.
Free vs Pro
| Feature | Free | Pro |
|---|---|---|
| Files per batch | 10 | 100 |
| LUFS targets | −14, −16, −23 | Custom |
| Dynamic range compression | — | |
| True peak limiting | — | |
| API access | — | |
| Watermark | None | None |
Frequently Asked Questions
Peak normalization looks at the loudest single sample in the audio and scales the entire file so that sample hits −0.1 dBFS. This maximises headroom but doesn't account for how loud the audio sounds overall — a file with many quiet sections but one brief loud peak will sound quiet after peak normalization. LUFS (Loudness Units) normalization measures the average perceived loudness across the whole file using a psychoacoustic model that weights frequencies similar to how human hearing works. Two files normalized to the same LUFS target will sound equally loud — this is why streaming platforms use LUFS, not peak, for their normalization.
Platform targets: Spotify normalises to −14 LUFS. YouTube normalises to −14 LUFS. Apple Music normalises to −16 LUFS. Tidal normalises to −14 LUFS. Apple Podcasts recommends −16 LUFS for speech. EBU R128 (European broadcast) specifies −23 LUFS. If a file is louder than the platform target, the platform turns it down — it won't be boosted above the target. So mastering to −14 LUFS means your audio won't be turned down on Spotify or YouTube, while still sounding loud on platforms with higher thresholds.
Normalization applies a single linear gain (volume multiplier) to every sample in the file. For WAV and FLAC, this is mathematically lossless — the relative amplitude differences between all samples are perfectly preserved. For MP3 output, the gain is applied and the audio is re-encoded, which introduces a small amount of additional compression. To avoid any quality loss, normalize to WAV output, then re-encode to MP3 if needed using our WAV to MP3 converter.
Normalization only adjusts overall gain — it cannot fix clipping distortion that has already occurred. If samples were clipped (amplitude exceeded 0 dBFS during recording), the waveform tops are flat and the harmonics of the distortion are baked into the audio. Normalization of an already-clipped file will reduce volume but the distortion will still be present. Clipping repair requires specialised tools that attempt to reconstruct the clipped waveform using the surrounding samples (declip processing), available in professional audio restoration software.
Normalization should be the last step — after all editing, mixing, effects, and mastering are complete. Applying normalization before editing means any subsequent processing (adding effects, EQ, compression) could change the levels again, requiring another normalization pass. The professional workflow for distribution is: record → edit → mix → master (EQ, compress, limit) → normalize to platform target → export and distribute.
Yes. TLS 1.3 encrypted. Files deleted within 24 hours. No watermarks. No account required.