Having used both, the experience of building actual UI with Flutter is a breeze compared to building UI in any game engine. I can imagine that most of the usage of Flutter is leveraging the huge amount of work that was already done to get efficient and capable UIs done with just a stack of widgets.
The places where it poses challenges in my experience are high quality typesetting/rich text, responsive UI that requires a wide range of presentations (i.e. different layout structures on mobile vs desktop), and granular control over rendering details.
But for functionality-oriented UI, it's hard to beat its simplicity and scalability, particularly when you want to develop on one platform (e.g. computer) and have everything "just work" identically on other form factors (web/tablet/etc.).
For example, Godot's editor is bootstrapped/built in Godot, and runs natively on Web, Android, and Quest XR among other platforms.
VIM does this perfectly. Not a single feature is exposed to the user. Every feature the user might ever want is supported, they need just Google for which keyboard incantation to invoke it.
Makes me wish more apps followed the UNIX model of separating every feature into separate applications with well documented interfaces that only change when new features absolutely require it and otherwise are only updated for security patches.
One common case I notice this is with FFMPEG. Everything that saves a video needs its own dialog with different settings. It would make a lot more sense if you had 1 single polished FFMPEG frontend that everyone just streamed data to.
On the other hand, I'm afraid that if this did happen that FFMPEG frontend would look like a GNOME app and I would hate using it.
Me, on the other hand, love ffmpeg, because I notice my ytdlp using it and my vlc player sometimes using it and I have two homemade powrshell scripts using it to convert flac to mp3 and whatever. I don't want to open a program and figure out it's UI for those things. It has a job, it does it well, you can sort of pipe things to it and I'm very happy.
I'm not sure you understood what I mean. I'm talking about applications like Krita using FFMPEG to export their data as video. Sometimes they include their own FFMPEG instead of using FFMPEG installed in the system. Each of them has its own dialog. The only way to input custom settings for FFMPEG would be to export in a lossless video format and then reencode using FFMPEG, when you should be able to just "connect" a data stream to an FFMPEG frontend as the input and the frontend has all the options you might want to customize how that data is turned into a .mp4 file or .mov file.
Want to generate a video, it's just a few lines of code. Want to connect the user's camera (with permission), it's just a few lines of code. Websockets? About 4 lines of code.
There could be 1000s of options for each of those but they mostly distilled it down to what most people need, and they're cross platform.
Over 60 AI models across 8 categories. The entire benchmark was built and runs inside of n8n and scores models on actual use cases in n8n rather than conversational style or subjective preference.
Smaller models often outperform larger models when it comes to specific tasks. We also found that a model's list price doesn't tell the whole story. One model priced at half the cost of competitors ended up being 10x more expensive in practice because it was so verbose in its outputs.
No single model dominates every category, so use the category filter on the benchmark page to find the best fit for your specific workflow. Whether you're building AI agents, automating data extraction, or generating code, this benchmark helps you make more informed decisions and build more cost-effective solutions.
Yep I had the same experience with Astro a couple years ago. Tried to deploy to Cloudflare and it was not working so ended up with Netlify. Tried again a few months ago and it worked flawlessly. Funny enough, they have since "bought" Astro and so I only expect it to get better
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