I created the ultimate AI stem splitter tools cheatsheet, so you find the best one for you
As a musician, I know the frustration of choosing the right stem splitting tool. With so many options available, it’s easy to feel overwhelmed.
But here’s the thing: picking the right stem splitter can help your music production workflow and unlock creative possibilities you never thought possible.
Download the cheatsheet here.
01 – What is stem separation actually?
Stem splitting is the process of separating a fully mixed audio track into its individual components, such as vocals, drums, bass, and other instruments. Think of it as having a magical audio surgeon that can precisely separate each layer of audio / music while maintaining pristine sound quality.
02 – 10 essential use cases for AI stem splitters:
AI stem splitting technology has changed various aspects of music production and content creation.
Here’s how different industries leverage this powerful tool:
| Use case | Example application |
|---|---|
| Professional remixing | Creating official remixes by isolating vocals from songs for modern reinterpretations |
| Live performance enhancement | Isolating instrumental tracks for live karaoke or backing tracks during concerts |
| Karaoke production | Removing vocals while maintaining high-quality instrumental tracks for karaoke applications |
| Film scoring | Extracting specific elements from soundtracks to enhance particular scenes or create new arrangements |
| Sample creation | Isolating unique sounds or instruments for use in new productions |
| Voice-over production | Separating dialogue from background music in existing content for dubbing or translation |
| Audio restoration | Cleaning up and enhancing individual elements of historical recordings |
| Educational analysis | Studying individual instrument parts for music education and transcription |
| Custom backing tracks | Creating professional-quality accompaniment tracks for performers |
| Content creation | Extracting specific elements for social media content, podcasts, or video productions |
03 – AI stem separation tool overview:
| Tool Name | Interface Type | Pricing Model |
|---|---|---|
| Audioshake | Web-based | Freemium |
| Fadr | Plugin | Premium |
| LALAL.AI | Web-based | Freemium |
| iZotope RX 11 | Plugin Module | Premium |
| Moises (Music.AI) | Web-based, App | Freemium |
| BandLab Splitter | Web-based, App | Free |
| Kits.AI | Web-based | Free |
| AudioStrip | Web-based | Freemium |
| Logic Pro 11 | Standalone | Premium |
| SpectraLayers 11 | Standalone | Premium |
| RipX DAW | Standalone | Premium |
| PEEL STEMS | Plugin | Premium |
Download the cheatsheet here.
04 – Stem splitting capabilities
Here’s a breakdown of AI stem separation tools and their splitting capabilities:
| Instruments | Music.AI | Logic Pro 11 | Spectralayers 11 | RX 11 Izotope | Lalal.ai | Fadr | Audioshake | AudioStrip | BandLab Splitter | PEEL STEMS | RipX DAW |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Vocals | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Bass | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Drums | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Other | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Guitar | ✅ | ❌ | ✅ | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ |
| Piano | ✅ | ❌ | ✅ | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
| Keys | ✅ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Wind | ✅ | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ |
| Strings | ✅ | ❌ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Electric Guitar | ✅ | ❌ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Acoustic Guitar | ✅ | ❌ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Kick | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Snare | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Toms | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Hi-hat | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Cymbals | ✅ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Cinematic Separation | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Guitar Solo/Rhythm | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
05 – Source separation benchmarks:
Signal-to-Distortion Ratio (SDR) is a crucial metric in evaluating the performance of AI stem separation tools. It quantifies how effectively an AI model can isolate individual instruments from a complete mix, with higher SDR values indicating cleaner separation.
A recent SDR benchmarking study (mentioned by Music.AI), such as those using the MUSDB18-HQ dataset, provided valuable insights into the capabilities of various models. This high-quality dataset, consisting of 150 uncompressed WAV files, offers a robust testing ground for AI separation algorithms.
However, it’s important to note that while SDR is a useful objective measure, it doesn’t always correlate directly with perceived audio quality. As an audio professional recently pointed out to me, the “best-sounding” model might not always have the highest SDR score.
That’s why I always recommend trying different tools yourself to find the one that best suits your specific needs and preferences. Each project may require a different approach, so hands-on experience with various models is invaluable.
06 – How to pick the right AI stem splitter
💰 Budget considerations:
- Free Tier: BandLab Splitter provides unlimited splits with basic separation capabilities, making it an accessible entry point for beginners and casual users.
- Mid-Range Solutions: LALAL.AI offers 10 minutes of free splitting with paid packages starting at $18 for 90 splitting minutes, providing professional-grade separation for vocals, instruments, drums, and bass.
- Premium Services: Audioshake offers an Indie tier starting at $20 monthly for basic access (4 stems), with advanced features in higher-tier plans, while also providing custom enterprise solutions for larger clients
🖖🏻 Separation quality:
- Test free tiers before purchasing to evaluate separation quality
- Consider the number of stems needed – some tools offer basic vocal/instrumental separation while others provide up to 10 individual stems
- Check supported file formats – most quality tools handle MP3, WAV, FLAC, and video formats
💻 Interface preferences:
- Web-based platforms like Kits.AI and BandLab offer immediate access without installation1
- Standalone software provides more robust features but requires local processing
- Mobile apps like Moises enable on-the-go stem splitting
🔉 Audio quality requirements:
- Check maximum file size limits (LALAL.AI supports up to 2GB)
- Verify output format options – professional work may require WAV or FLAC
- Consider processing speed needs – premium tiers often offer faster processing
Additional selection criteria
- Evaluate batch processing capabilities for multiple files
- Check integration options with your existing DAW or workflow
- Consider community support and regular updates
- Look for additional features like pitch/tempo adjustment that may add value
Remember, the most expensive option isn’t always the best choice – select a tool that matches your specific workflow needs and production requirements.
