What's better, FlutterFlow or DreamFlow?
What's better, FlutterFlow or DreamFlow?
What's better, FlutterFlow or DreamFlow?
By
Erik Goins
Published on:
Oct 22, 2025
Last week I had a fun conversation with an existing Flywheel Studio client with a FlutterFlow mobile app - what’s next for their app? As they scale, should they stay on FlutterFlow? Should they go native? Is there something else out there?
This gave me the chance to run a fun experiment I’ve been thinking about for some time now. I’ll come back to the experiment shortly, but first, I want to talk about how we discuss this with clients today.
Does FlutterFlow Scale?
This is the most frequently asked question we get and it makes a lot of sense. If you’re investing in a mobile app, you don’t want to choose a platform that won’t scale with your aspirations.
In short, FlutterFlow produces highly scalable applications. We’ve never seen a client leave FlutterFlow for performance reasons.
The more detailed point is that FlutterFlow doesn’t actually run your mobile app. It writes Flutter code, using visual development, which runs locally on each user’s phone. Your backend, typically Firebase or Supabase, is what handles the workload of each additional user.
Firebase and Supabase are highly scalable, handling applications into the tens of thousands and millions of users. Firebase runs on Google Cloud and Supabase runs on AWS. We like to say that if you outgrow Google Cloud or AWS then you’ve hit a good problem to have.
All of this said - scalability is more in application design than the platform. It’s easy to design a platform that doesn’t scale. This is where expertise with high volume and usage application is key and we’ve got you covered on this.
The Experiment
Years ago a popular flutter developer wrote a scathing review of FlutterFlow’s code quality. I believe it was misguided. It was like a literary critique’s review of a popular book - sure, it might not have the best writing but if it’s popular and it works, is that so bad?
We know FlutterFlow isn’t perfect and that’s okay. Recently, FlutterFlow released DreamFlow though. A similar but different platform that focuses on more native flutter development and less visual development the way FlutterFlow handled it.
For more information about DreamFlow, we’ve written an article here “Is AI the Future of Mobile App Development? A Deep Dive into FlutterFlow's DreamFlow”.
With the option of two different platforms, I wanted to run an experiment to compare the code quality. This is typically difficult because:
We don’t have the “same” app on both platforms
How do you compare two different app’s code bases in an unbiased way?
I decided to let AI do the comparison. I used Gemini CLI to do this.
Methodology
I took two apps of similar complexity. One from FlutterFlow and the other from DreamFlow.
They have several screens, logic and calculations, and use Firebase. They’re as close as we could get without rebuilding the same app twice.
We also used the same prompt and model for comparison. We chose an open ended prompt “Review the code for Flutter and Dart code quality. How would you rate the code quality and what can be improved?” and we used Gemini 2.5 Pro for the evaluation.
The Results
FlutterFlow
Gemini rated the code ⅖ (Poor). It’s verbose, difficult to read, business logic is scattered throughout the code, and monolithic state management. To name a few of the things Gemini raised.
DreamFlow
Gemini rated the code quality as Good. It recommended improved state management, overlap between models in the code, security issues, and error handling.
The security issue raised was concerning. Anytime you read “hard coded API keys” you should be scared. I decided to dig deeper and see what the issue is.
Luckily, it was a false alarm. The keys were supposed to be public and we hadn’t hardened the Firebase security rules for these test apps so everything raised was okay.
The Outcome
Now, you can see the outputs from Gemini clearly but there’s a lot left unsaid or not taken into account.
First, Gemini’s feedback for FlutterFlow focuses on maintainability and readability of the code. I’m sure this makes sense for a traditional code base but in FlutterFlow and how we develop with the platform, this feedback isn’t helpful.
When you’re developing on FlutterFlow, you don’t read the underlying code. You see the visual representation of it in the editor. Overly verbose, readability, and maintainability aren’t critical the way Gemini references.
In fact, we find it easier to maintain apps in FlutterFlow compared to traditional code bases. In traditional development, every developer has their own structure and methodology. In FlutterFlow’s visual development editor, it’s easy to pick up a project and see the widgets, custom code, screens, and actions.
DreamFlow’s feedback was a little more surprising. I know FlutterFlow develops with building blocks which would make it verbose, but DreamFlow has the advantage of writing code from scratch and without any of those limitations. In theory, it should be perfect.
The state management, code duplication, and error handling is opinionated feedback. This has been a common problem in vibe coding. AI will generate code but builder beware. You’re still responsible for being a good developer.
What did we tell our client?
Based on their application’s use cases, we expect they’ll be able to scale without issues on FlutterFlow. The same as our other clients have in the past.
That said, when DreamFlow adds a few critical features (version control, project import, collaboration, etc.) we’re going to try importing our client’s project to DreamFlow and see what happens.
Will DreamFlow accept the project without issues?
Will we need a complete refactoring to run it? And can DreamFlow refactor it?
Is the new app in DreamFlow better than the old one in FlutterFlow?
That’ll be the next experiment!
Last week I had a fun conversation with an existing Flywheel Studio client with a FlutterFlow mobile app - what’s next for their app? As they scale, should they stay on FlutterFlow? Should they go native? Is there something else out there?
This gave me the chance to run a fun experiment I’ve been thinking about for some time now. I’ll come back to the experiment shortly, but first, I want to talk about how we discuss this with clients today.
Does FlutterFlow Scale?
This is the most frequently asked question we get and it makes a lot of sense. If you’re investing in a mobile app, you don’t want to choose a platform that won’t scale with your aspirations.
In short, FlutterFlow produces highly scalable applications. We’ve never seen a client leave FlutterFlow for performance reasons.
The more detailed point is that FlutterFlow doesn’t actually run your mobile app. It writes Flutter code, using visual development, which runs locally on each user’s phone. Your backend, typically Firebase or Supabase, is what handles the workload of each additional user.
Firebase and Supabase are highly scalable, handling applications into the tens of thousands and millions of users. Firebase runs on Google Cloud and Supabase runs on AWS. We like to say that if you outgrow Google Cloud or AWS then you’ve hit a good problem to have.
All of this said - scalability is more in application design than the platform. It’s easy to design a platform that doesn’t scale. This is where expertise with high volume and usage application is key and we’ve got you covered on this.
The Experiment
Years ago a popular flutter developer wrote a scathing review of FlutterFlow’s code quality. I believe it was misguided. It was like a literary critique’s review of a popular book - sure, it might not have the best writing but if it’s popular and it works, is that so bad?
We know FlutterFlow isn’t perfect and that’s okay. Recently, FlutterFlow released DreamFlow though. A similar but different platform that focuses on more native flutter development and less visual development the way FlutterFlow handled it.
For more information about DreamFlow, we’ve written an article here “Is AI the Future of Mobile App Development? A Deep Dive into FlutterFlow's DreamFlow”.
With the option of two different platforms, I wanted to run an experiment to compare the code quality. This is typically difficult because:
We don’t have the “same” app on both platforms
How do you compare two different app’s code bases in an unbiased way?
I decided to let AI do the comparison. I used Gemini CLI to do this.
Methodology
I took two apps of similar complexity. One from FlutterFlow and the other from DreamFlow.
They have several screens, logic and calculations, and use Firebase. They’re as close as we could get without rebuilding the same app twice.
We also used the same prompt and model for comparison. We chose an open ended prompt “Review the code for Flutter and Dart code quality. How would you rate the code quality and what can be improved?” and we used Gemini 2.5 Pro for the evaluation.
The Results
FlutterFlow
Gemini rated the code ⅖ (Poor). It’s verbose, difficult to read, business logic is scattered throughout the code, and monolithic state management. To name a few of the things Gemini raised.
DreamFlow
Gemini rated the code quality as Good. It recommended improved state management, overlap between models in the code, security issues, and error handling.
The security issue raised was concerning. Anytime you read “hard coded API keys” you should be scared. I decided to dig deeper and see what the issue is.
Luckily, it was a false alarm. The keys were supposed to be public and we hadn’t hardened the Firebase security rules for these test apps so everything raised was okay.
The Outcome
Now, you can see the outputs from Gemini clearly but there’s a lot left unsaid or not taken into account.
First, Gemini’s feedback for FlutterFlow focuses on maintainability and readability of the code. I’m sure this makes sense for a traditional code base but in FlutterFlow and how we develop with the platform, this feedback isn’t helpful.
When you’re developing on FlutterFlow, you don’t read the underlying code. You see the visual representation of it in the editor. Overly verbose, readability, and maintainability aren’t critical the way Gemini references.
In fact, we find it easier to maintain apps in FlutterFlow compared to traditional code bases. In traditional development, every developer has their own structure and methodology. In FlutterFlow’s visual development editor, it’s easy to pick up a project and see the widgets, custom code, screens, and actions.
DreamFlow’s feedback was a little more surprising. I know FlutterFlow develops with building blocks which would make it verbose, but DreamFlow has the advantage of writing code from scratch and without any of those limitations. In theory, it should be perfect.
The state management, code duplication, and error handling is opinionated feedback. This has been a common problem in vibe coding. AI will generate code but builder beware. You’re still responsible for being a good developer.
What did we tell our client?
Based on their application’s use cases, we expect they’ll be able to scale without issues on FlutterFlow. The same as our other clients have in the past.
That said, when DreamFlow adds a few critical features (version control, project import, collaboration, etc.) we’re going to try importing our client’s project to DreamFlow and see what happens.
Will DreamFlow accept the project without issues?
Will we need a complete refactoring to run it? And can DreamFlow refactor it?
Is the new app in DreamFlow better than the old one in FlutterFlow?
That’ll be the next experiment!