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Dyad is worth considering if you want an AI app builder whose project files stay on your computer, whose generated code can leave the app, and whose model choice is not tied to one hosted service. It is less compelling if you want a zero-setup, all-inclusive service or expect a guaranteed level of generated-code quality. Dyad lists a free desktop tier, a $20-per-month Pro tier and a $79-per-month Max tier, but paid plans and included credits should be checked on the official pricing page immediately before subscribing.
The important distinction is that “local” describes more than one thing. Dyad runs as a desktop application and keeps project files locally, while inference can use a hosted provider or a model running through Ollama or LM Studio. A hosted model sends prompts and relevant project context to that provider; a local model can work offline but depends on your computer and model setup. This review explains those trade-offs, the license details behind the open-source label, and a practical way to decide whether Dyad fits your project.
What Dyad is
Dyad is a desktop AI app builder that turns a plain-language description into application code and a live preview on your own machine. The normal loop is conversational: describe a screen or feature, let the model generate or change files, inspect the running preview, then ask for another change. Dyad presents this as a local, open-source alternative to browser-first app builders.
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The core workflow
- Describe the app. Write a natural-language specification such as the pages, data fields, navigation and visual style you want.
- Generate code. Dyad asks the selected AI model to create or modify project files.
- Run the preview. The desktop app displays the generated project locally so you can check the result.
- Iterate. Report a concrete problem or request a focused change rather than repeatedly restating the entire idea.
- Continue outside Dyad. Keep the files on disk, open them in a conventional editor and export or otherwise carry the code into a normal development workflow.
That loop is useful because it combines a visual feedback cycle with ownership of ordinary files. It does not remove the need for testing, dependency management, authentication setup, deployment configuration or code review once an app moves beyond a prototype.
How “local” actually works
Dyad’s local-first design has three separate parts: the desktop interface, the project files and model inference. Treating them as one thing leads to incorrect privacy and cost assumptions.
Local desktop app and files
Dyad offers downloads for macOS, Windows and Linux. Its product information says projects remain on disk, existing repositories can be imported and code can be exported for continued work in an editor. Those properties make the project more portable than a design that exists only inside a vendor account.
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Hosted-model inference
Dyad lists OpenAI, Anthropic and Google among its model options. When you select a hosted model, your prompt and whatever project context the integration sends travel to that provider. The request may incur that provider’s usage charges and is subject to its data-handling terms. Running the Dyad interface locally does not make that inference path offline.
The free plan is described as allowing you to bring your own API key. In that arrangement, Dyad may not charge you for model usage, but the provider can still bill your account. The available product information does not establish current rates, retention policies or contractual terms for any provider, so check the provider documentation before sending sensitive source code.
Local-model inference
Dyad also lists Ollama and LM Studio. A model served through one of those tools can run on your computer and can work offline after the model is installed. Offline operation is conditional: the model must be downloaded, the local server must be running and your hardware must be able to handle the model within a reasonable time.
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Local inference trades subscription and network dependence for setup work and finite local compute. Smaller models may be easier to run but can require more correction; larger models can demand substantial memory and run slowly. Dyad does not publish a universal hardware matrix in the information available here, so test the exact model and project on your own machine rather than assuming that “local” means fast.
What remains portable
Because the project is represented by files on disk, you can back it up, put it under version control and open it in another editor. Portability is a practical reduction in platform lock-in, not a promise that every generated dependency or service integration will work unchanged elsewhere. Review package licenses, environment variables, database connections and build scripts before handing the project to another team or deployment system.
Getting started without losing control
The following sequence keeps the first experiment small and makes it easier to judge whether Dyad is useful for your kind of work.
1. Install the desktop build
- Download the build for macOS, Windows or Linux from Dyad’s official site.
- Choose a project directory on a drive that is backed up and has enough space for the generated source, dependencies and any local model files.
- Open the application and confirm that you can locate the project files on disk. Knowing the path before generating code makes later inspection and backup straightforward.
2. Choose an inference path
- Bring a hosted API key: configure the provider you already use and expect that provider’s normal usage billing and data terms.
- Use a local server: install and configure Ollama or LM Studio, download a compatible model and point Dyad to the local endpoint. This can support offline work but uses your machine’s resources.
- Use a paid Dyad plan: review the current credit allowance and what each mode includes before assuming model usage is covered.
Keep credentials out of source files. Use the provider’s supported key storage or environment-variable mechanism, and remove a key immediately if it is exposed in a repository or prompt transcript.
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Ask for one user journey rather than an entire production platform. Specify the target screen, fields, validation rules, sample data and success condition. For example, request a task list with create, complete and filter actions, then verify each action in the preview. A bounded request gives you a meaningful measure of how much correction the model requires.
4. Inspect every generated change
Use the project directory and your normal editor to read the files Dyad created. Check routing, state handling, error paths, dependencies and configuration. Generated code that looks correct in a preview can still contain insecure defaults, missing validation or an architecture that will be difficult to extend.
5. Export and run the project independently
Open the exported code outside Dyad, install its dependencies and run its documented development command. If it cannot start without the app, identify what is missing before investing in a larger build. This test measures the portability that is central to Dyad’s value proposition.
6. Record the cost and correction rate
For each task, note the number of prompts, the model used, the time spent fixing output and any provider charges. A tool that produces a first draft quickly can still be poor value if every feature requires extensive manual repair. Your own project log is more useful than a generic claim about AI accuracy.
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Dyad plans and listed prices
The homepage currently lists the following terms. Prices, credit quantities and included features can change, so verify them on publication day or immediately before purchase.
| Plan | Listed price | Included terms | Best fit |
|---|---|---|---|
| Dyad Free | Free | Desktop app; no sign-up is stated for the plan; bring your own API key; community support | Trying the workflow with your own provider or a local model |
| Dyad Pro | $20 per month | 200 AI credits per month, Pro modes for large codebases and Dyad Academy access | Regular users who need the paid modes and a monthly credit allowance |
| Dyad Max | $79 per month | 900 AI credits per month and prioritized office-hours access, in addition to Pro features | Heavy users who value more included credits and priority assistance |
The homepage says credits can be reloaded. The amount of work represented by one credit is not established in the available information, so 200 credits should not be translated into a fixed number of screens, prompts or hours. Ask how credits are consumed by the specific mode and model you plan to use.
What the free route really costs
“Free” refers to Dyad’s listed software tier, not necessarily to the whole workflow. With a hosted provider, you can owe that provider for token usage. With a local model, you pay in setup time, storage, electricity and the opportunity cost of slower generation. If you already have a suitable local model or API account, the free tier can be an inexpensive way to evaluate the interface. If not, compare the complete monthly and operational cost rather than the subscription line alone.
When Pro or Max can make sense
Pro is easier to justify when large-codebase modes or Academy access address a recurring need and 200 monthly credits cover your normal iterations. Max adds 700 credits over Pro’s listed allowance and prioritized office-hours access, but its value depends on actually using those benefits. Neither price proves superior generated code; the official information provides no independent benchmark linking a plan to output quality.
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Dyad can accurately be described as an open-source project, but the repository does not place every directory under one identical license. Code outside src/pro is licensed under Apache 2.0. Code inside src/pro is under Functional Source License 1.1 Apache 2.0.
That distinction matters if you plan to fork, modify or redistribute a particular Pro component. Read the license file that applies to the exact path you will use, and obtain legal advice for a commercial redistribution decision. Do not assume that the permissions for the general repository automatically apply to files in src/pro.
The license issue is separate from whether generated application code is useful. You should also inspect the licenses of frameworks, packages, fonts, model outputs and other assets pulled into the generated project.
Privacy and lock-in: what Dyad supports and what it does not prove
Evidence for a local-first design
- Projects are described as remaining on your computer.
- Existing repositories can be imported.
- Code can be exported for work in an editor.
- Hosted and local model paths are both listed.
Together, those features support a local-first design and make it easier to keep a conventional copy of your project. They also let you select a model source instead of accepting one mandatory provider.
Limits of the privacy claim
Local files do not guarantee that no information leaves the computer. A hosted model necessarily receives the request and any context sent with it. Plugins, package managers, error-reporting services, deployment platforms and external databases can create additional network paths. Before using proprietary code or personal data, map the exact integrations in your workflow and read their current terms.
A local model reduces the need to transmit prompts to a hosted inference service, but it does not automatically secure the machine, the local server or backups. Protect the project directory, rotate keys and treat downloaded models and dependencies as software that requires normal security hygiene.
How much lock-in is reduced
Keeping files in a normal directory and exporting code is a meaningful advantage over a system that stores the only copy in a proprietary workspace. It does not eliminate lock-in to a framework, database, deployment service or model-specific behavior. Use version control, document environment variables and test a clean checkout so that leaving Dyad is a practical operation rather than a theoretical possibility.
What is known about generated-code quality
The available official material explains Dyad’s workflow and plans but does not provide an independent benchmark, controlled comparison or named performance statistic. There is therefore no evidence-based percentage for first-pass success, a guaranteed speed advantage or a claim that Dyad produces better code than another builder.
You can evaluate quality systematically with a small acceptance suite:
| Test | What to inspect | Why it matters |
|---|---|---|
| Basic feature | Does the requested action work in the preview and after restarting the project? | Separates a visual mock-up from functioning code. |
| Validation and errors | Are empty, malformed and failed inputs handled clearly? | Exposes brittle happy-path generation. |
| Change request | Can you add a feature without breaking an existing one? | Measures maintainability during iteration. |
| Independent run | Does the exported project run in your editor or terminal? | Tests portability beyond Dyad’s preview. |
| Security review | Are secrets, permissions and user-controlled data handled safely? | Prevents a convincing demo from becoming an unsafe release. |
| Cost tracking | How many prompts, credits and provider charges did the feature require? | Turns “fast” into a measurable value decision. |
Run the same suite on a representative project, not a toy screen, before paying for a higher tier. Keep the prompts and resulting commits so you can compare model changes or plan changes later.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Who should use Dyad
Strong fit
- You want a visual, conversational starting point but insist on owning ordinary project files.
- You are comfortable configuring an API key or local model server.
- You value choosing between hosted inference and an offline-capable local model.
- You can review generated code and take responsibility for testing and deployment.
- You expect to move the project into a conventional editor or repository.
Weak fit
- You need a fully managed service with no provider account, model setup or local configuration.
- You require a published guarantee about privacy, uptime or generated-code correctness.
- You cannot review code, dependencies or authentication settings before release.
- Your organization needs confirmed hardware, compliance or retention specifications that Dyad’s public product information does not state.
- You expect a subscription tier alone to guarantee better output without measuring your own workload.
A practical 30-minute value test
- Choose one realistic feature. Use a small workflow from your intended app, including at least one validation rule and one error state.
- Run it on the free path. Use your own key or a local model, and write down setup time, model and any external cost.
- Check the files. Confirm where the project lives, whether it starts independently and whether the code is understandable enough to edit.
- Make two changes. Request a normal feature addition and a bug fix. Record what the model breaks and how much manual repair is required.
- Estimate a month. Compare your observed credit use and provider charges with the current Pro and Max allowances, without assuming that credits map linearly to features.
- Decide by workflow, not novelty. Subscribe only if the saved time, model access or support benefit exceeds the recurring price for your actual projects.
Common pitfalls and recovery steps
Assuming local means fully offline
Symptom: a hosted provider is configured while the user expects no network transfer. Fix: switch to a locally served model, verify that the server is local and disconnect the network for a controlled test. If the project depends on remote packages or services, document those remaining connections.
Exposing an API key
Symptom: a key appears in source, a screenshot or a prompt. Fix: revoke or rotate it at the provider immediately, remove it from files and history, and use secure environment configuration going forward. Assume a copied key is compromised.
Judging quality from the first preview
Symptom: the screen looks right but actions fail after reload or outside the preview. Fix: test persistence, validation, error handling and an independent run before adding more features.
Running out of credits unexpectedly
Symptom: a large request or repeated retries consume the allowance faster than expected. Fix: split work into smaller changes, track usage per task and confirm how the selected mode counts credits. Reload only after checking the current price and your expected monthly workload.
Overlooking license boundaries
Symptom: a team assumes every repository file has Apache 2.0 permissions. Fix: inspect the license applying to the exact directory, especially src/pro, before modifying or redistributing it.
Final verdict
Dyad’s strongest case is control: local project files, exportable code and a choice between hosted providers and local models. That combination can be valuable to a builder who wants AI assistance without surrendering the project to a single browser workspace. The free tier is a sensible starting point when you already have a provider key or local model.
The decision becomes less favorable when convenience matters more than control, when provider setup is a barrier or when you need independently verified performance and privacy guarantees. Pro at $20 per month and Max at $79 per month may be reasonable for sustained use, but the listed 200 and 900 monthly credits cannot be translated into value without measuring your own tasks. Treat Dyad as a tool to evaluate on a representative project, inspect the generated code, and keep a portable copy—not as a substitute for engineering judgment.
Quick Recap
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