Teachable Machine
Train custom ML models in your browser, no coding required.
Best for quick prototyping and classroom demos. Teachable Machine is the most accessible way to train a custom classifier—no sign-up, no GPU, no code. But it caps at 10 classes and can't handle large datasets or complex tasks. If you need production-grade accuracy or advanced architectures, consider Google's AutoML or a custom TensorFlow pipeline. For learning or a fast proof of concept, this is unbeatable.
Verified 18d ago · liveness 69/100 · cite: rightaichoice.com/tools/teachable-machine
- Educators teaching ML concepts without code
- Artists and creatives building interactive installations
- Students prototyping ML ideas for class projects
- Non-programmers exploring quick ML proofs-of-concept
- Production applications requiring high accuracy and large datasets
- Complex multi-label or multi-object detection tasks
- Real-time applications needing low latency and optimization
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Skip Teachable Machine if you need a production-grade ML model with high accuracy, large datasets, or custom architectures.
No hidden costs; tool is entirely free.
Teachable Machine is completely free—no tiers, no paywalls. Ideal for education, prototyping, and hobbyists. For teams needing advanced features like collaboration or larger datasets, paid alternatives like AutoML or Clearly offer more but cost money.
In short
Teachable Machine — Train custom ML models in your browser, no coding required. Best for Educators teaching ML concepts without code, Artists and creatives building interactive installations, Students prototyping ML ideas for class projects. Free to use.
Viability Score
How likely is Teachable Machine to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Train image, audio, and pose models without code
- Real-time training feedback in the browser
- Export models as TensorFlow.js or TensorFlow Lite
- Use webcam or microphone for live data collection
- Upload image and audio files for training
- Preview model predictions in real time
- Create classes and add examples via recording
- Share models via URL or download
- Works offline after initial load
- No account or login required
- Up to 10 classes per model
- Integrates with Glitch, p5.js, and more
About Teachable Machine
Teachable Machine is a free, web-based tool from Google that lets you train machine learning models using your own images, sounds, or poses—all in the browser with no code. Designed for educators, artists, students, and makers, it provides real-time training feedback and immediate classification. You can use your webcam or microphone to collect training data, or upload files. Models can be exported as TensorFlow.js or TensorFlow Lite for use on websites, apps, and edge devices. While limited in complexity, it's an excellent entry point for prototyping ML ideas and teaching AI fundamentals.
Behind the Verdict
Teachable Machine is a masterclass in removing barriers. You open the site, click a button, and start collecting data with your webcam or mic. Training happens in seconds, and you see predictions update live. This makes it perfect for classrooms, workshops, and art projects where the goal is understanding ML concepts, not building a deployable system. The export options (TensorFlow.js, TFLite) are genuinely useful—you can embed your model into a p5.js sketch, a Glitch app, or even a Coral AI device. That said, the simplicity comes with hard limits: maximum 10 classes, no custom architectures, no hyperparameter tuning, and you're stuck with image, audio, and pose inputs only. Chrome or Safari on desktop is required; mobile support is nonexistent. It also lacks collaboration features, version control, or any data management beyond one session. For tech teams evaluating ML tools, this is not for production. But for anyone who wants to 'try' machine learning without any overhead, it's the place to start. Think of it as the 'Hello World' for custom models.
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Real-world workflow fit
Concrete scenarios for the personas Teachable Machine actually fits — and what changes day-one when you adopt it.
During a 45-minute class, the teacher demonstrates image classification. Students take photos of their own handwritten digits, train a model, and test it with new samples—all without installing software.
Outcome: Students grasp the concept of training vs. inference in a single session, building a working classifier they can share via URL.
An art student uses the webcam to collect poses (e.g., raising hands, jumping) and trains a pose classifier. They export the model to p5.js and map predictions to visual effects (e.g., changing colors on screen).
Outcome: A responsive art piece that changes based on the viewer's movements, completed in an afternoon with no coding skills.
Use Cases
- Teach AI basics in a classroom without any coding
- Create a gesture-controlled game using pose detection
- Build a sound-activated light show for an art project
- Prototype an image classifier for sorting objects on a webcam feed
- Quickly demonstrate ML concepts at workshops or hackathons
- Enable non-technical team members to experiment with ML
- Design an interactive museum exhibit that responds to visitor poses
Models Under the Hood
as of 2026-07-14
Limitations
- Teachable Machine cannot handle large datasets or complex model architectures.
- It supports only image, sound, and pose inputs.
- No custom neural network layers or hyperparameter tuning.
- Requires Chrome or Safari on desktop for full functionality.
- Model accuracy is limited by the simplicity of the training process.
- Limited to 10 classes per model.
as of 2026-06-25
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Teachable Machine tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free Access
$0/mo
Ideal for
Solo educator, hobbyist, or student exploring ML with no budget
What this tier adds
Free entry point with full training and export capabilities, but limited to 10 classes per model.
Where the pricing makes sense
The company stage and team size where Teachable Machine's pricing actually pencils out — and where peers do it cheaper.
Teachable Machine is completely free—no tiers, no paywalls. Ideal for education, prototyping, and hobbyists. For teams needing advanced features like collaboration or larger datasets, paid alternatives like AutoML or Clearly offer more but cost money.
Setup time & first value
How long it actually takes to get something useful out of Teachable Machine — broken out by persona, not the marketing-page minute.
From opening the site to having a working model: under 5 minutes for a simple image or sound classifier. Adding more classes or data may take 10–15 minutes. Export and integration add another 10 minutes if you follow the example code. No account creation needed.
Switching to or from Teachable Machine
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Scratch: Start fresh with no prior ML experience—import your own images/sounds or collect live data.
- ↗To TensorFlow: Download the model as a .h5 or SavedModel from the export menu, then retrain with Keras for more complex architectures.
- ↗To AutoML: Use the exported data (images/sounds) as a starting dataset for Google AutoML Vision or Audio for higher accuracy and larger scale.
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