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 4h ago · liveness 76/100 · 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 production-grade accuracy, handle large datasets, require multi-label or multi-object detection, or need collaboration features—it caps at 10 classes and runs only on desktop Chrome or Safari.
There are no hidden costs—Teachable Machine is completely free with no account required.
Teachable Machine is free for anyone—no account, no credit card. It fits educators, students, and hobbyists better than paid tools like Google AutoML or custom TensorFlow pipelines, which cost money and require ML expertise.
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 well maintained and how widely used is Teachable Machine? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Train image classification models using files or webcam
- Train audio classification models via microphone
- Train pose classification models using webcam
- Real-time training feedback and classification preview
- Export models as TensorFlow.js (JavaScript) and TensorFlow Lite
- Use with tools like Glitch, p5.js, and Node.js
- Integrate with Arduino and Coral for edge deployment
- Works offline after initial load
- No account or login required
- Up to 10 classes per model
- Share models via URL or download as file
- Uses webcam or microphone for live data collection
- Upload image and audio files for training
- Desktop browser support (Chrome, Safari)
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 like Arduino and Coral. While limited in complexity, it's an excellent entry point for prototyping ML ideas and teaching AI fundamentals. Note: The tool currently requires desktop Chrome or Safari; it is not supported on mobile or other browsers.
Behind the Verdict
Teachable Machine shines as an on-ramp to machine learning. The entire training loop happens in your browser, which means zero setup friction—you can go from zero to a working image classifier in minutes. The real-time feedback is genuinely impressive: you see accuracy update as you add samples, which makes it a fantastic teaching tool. Strengths: It's free, requires no account, and models export to TensorFlow.js and TensorFlow Lite, so you can deploy to web or edge devices. The pose and audio modes extend beyond simple image classification, covering a surprising range of interactive projects. For educators, it's a killer demo—students grasp the concept of training data almost immediately. For artists and makers, it's an easy way to add gesture or sound control to installations. Weaknesses: The 10-class cap and the requirement to run on desktop Chrome or Safari are real constraints. Training data is limited to what you can collect in-browser, and there's no support for large datasets or transfer learning from pre-trained models. For production, you'd hit a wall quickly. Also, the lack of collaboration features means it's solo-only. Where it fits: workshops, hackathons, classrooms, and quick proofs-of-concept. It's the fastest way to validate an ML idea before committing to a heavier pipeline. Where it doesn't: any serious production workload, complex vision tasks, or team-based ML development.
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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.
Preparing a hands-on ML lesson for a middle school class
Outcome: Create an image classifier by uploading a few photos per class, show real-time training, and have students test it live on webcam—no coding required.
Building an interactive installation that responds to visitors' poses
Outcome: Train a pose model using webcam samples, export it as TensorFlow.js, and embed it in a p5.js sketch to trigger visuals or audio based on detected poses.
Prototyping a gesture-controlled game
Outcome: Use webcam to record gestures, train a pose classifier in minutes, and export to Glitch to deploy a playable web game.
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 2026-08-31
Limitations
- The Teachable Machine website currently displays a compatibility warning stating that the tool is not supported on the current browser or device, and recommends visiting on desktop in Chrome or Safari.
- No other specific limitations are detailed in the provided evidence.
as of 2026-08-28
Verification history
We have re-verified Teachable Machine 19 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
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- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 19 verification passes.
Free to cite with attribution — this page re-verifies continuously.
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
$0/mo
Ideal for
Anyone wanting to learn ML basics or prototype a quick idea without commitment—students, educators, artists, and hobbyists.
What this tier adds
The only tier; completely free with no account required, allowing up 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 free for anyone—no account, no credit card. It fits educators, students, and hobbyists better than paid tools like Google AutoML or custom TensorFlow pipelines, which cost money and require ML expertise.
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.
You can be up and running within 5 minutes: open the site, record samples, train, and test. No account or installation needed. For a full classroom activity, budget 30-60 minutes including explanation and experimentation.
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 or block-based tools: Start with familiar concepts, then move to Teachable Machine for real ML training.
- →From Google's ML Kit: If you're new to ML, Teachable Machine offers a simpler, browser-based alternative for prototyping.
- ↗To Google AutoML: Export your Teachable Machine dataset and retrain with AutoML for higher accuracy and scale.
- ↗To Custom TensorFlow: Download your model and use it as a starting point for fine-tuning or integration into larger pipelines.
Integrations
Resources & Guides
Tutorials & Learning
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