ianberdin

I've seen people on Reddit writing things like, "Come on, what's the big deal? AI can write any code now." I disagree. There are hundreds of thousands of lines of code here, very complex code, which even AI wouldn't be able to write on the first try or in a single day. So this person stole this code from Photopea and built a product on top of it.

https://playcode.io/blog/macbook-svg-benchmark#model-claude-...

Btw, we have added Opus 5.5 as default model to playcode.ai

MacBook Pro 3D in SVG for me the most helpful one.

https://playcode.io/blog/macbook-svg-benchmark

Everyone knows how a MacBook looks. Any missing or incorrect detail will be obvious. However, Pelican or this world can be anything.

https://playcode.io/blog/macbook-svg-benchmark

This platform powers full-stack applications for business users, including Playcode.ai.

For more information about our cloud platform, visit: https://playcode.io/cloud

Take Bun, for example. Nobody is actually running it in production as a runtime. Why? Memory leaks and a whole bunch of other issues. I've personally tried it multiple times, and something always breaks. Come on, it's just not that simple.

Sure, you can build something that has similar interfaces and even works to some degree. But making a production-ready solution is a completely different level of complexity. There's that well-known chart where the first 90% of implementation happens almost instantly, and the remaining 10% takes forever to polish out all the rough edges.

On one hand, I really like the idea, and I've always wondered why TypeScript doesn't compile to native code. On the other hand, I'm quite skeptical that Vercel can actually pull this off. I'd be happy to be proven wrong, but I have very little faith in it.

Either way, good luck to them, but honestly, even if they succeed, I probably won't use it. Knowing their track record with vendor lock-in and Next.js, where they do everything possible to push you onto Vercel Cloud — no thanks.

Fable is not better, it says zero information between steps and then output a summary. A perfect “send - done”.

It creates the MacBook svg way better than 4.8, yet only fable can make it perfect without visual defects. Results similar to Kimi K3.

Same pelican grid + MacBook Pro in 3D. Also with end cost.

https://playcode.io/blog/macbook-svg-benchmark

Fable 5 still wins on detail with no visible errors, but it's close. And this isn't a memorized pelican;

https://playcode.io/blog/macbook-svg-benchmark#gemini-3-6-fl...

One way or another, I want to note that yes, this text was made in collaboration with AI. My English is non-native. It helps me translate, helps me structure better. Yes, there is a downside, it can bloat the text with unnecessary words. But that, unfortunately, is the price.

But the key thing is that I tried very hard to share my many years of experience, or rather a part of it, which I acquired, with all of you. And I am very glad that this information turned out to be useful to you.

The key here is: * The information that is written in the article. * Not how it is written, but what I was trying to convey to you.

Thank you very much for reading and responding.

It is actually a big result of work, a lot of research and attempts. And to just say that "oh, this is AI-slop," I consider unfair, but that is your choice.

There is a difference: - There are people who do, - And there are those who criticize.

Today, I tested Sol 5.6 on various tasks. It performs similarly to Opus 4.8 but is still noticeably more expensive than Sonnet 5. Although Sonnet 5 isn't the top model, it's quite effective for creating typical websites for small and medium businesses. However, they will increase the price starting September 1, as their free offer is ending.

I'm also actively testing Grok 4.5. There's something promising about it. The design is mediocre, in my opinion, but it operates quickly and reliably without any deadloops. Usually, Grok models would fail or loop, but this one is stable.

Overall, I really want a benchmark based on real tasks.

On one hand, the price is just astronomical for Fable, well, not exactly astronomical, but I would say unaffordable. That is to say, so expensive that it is impossible to use.

But on the other hand, Fable is simply incomparable to anything else. I mean, it is just amazing. There is nothing even close to being equal to it.

Of course, these are my guesses, but did anyone feel the difference in the transition from Opus 4.5 to 4.6? In my opinion, no. And it's unlikely to be a matter of the tokenizer.

When an issue arises, I often test the systems by providing a minimal prompt, like: "this user, this is their email, this isn't working, figure it out in production." I send this to both Opus and ChatGPT, but it doesn't help. I've set up Agents.md and Quote.md identically, with the same access and linkers, so the Harness is consistent.

ChatGPT rarely succeeds. If the task is complex and requires a multi-step process to identify the true cause, ChatGPT usually stops after a few initial ideas and wrongly claims it has found the solution.

- For simple tasks, like identifying a missing item in a to-do list, ChatGPT performs well. - However, for issues like memory leaks or file system corruption, it struggles.

On the other hand, Opus 4.8 always finds the solution, albeit slowly. I can rely on it without worrying about whether it will succeed. It just gets the job done.

Recently, Fable 5 has emerged, which resolves issues without needing any prompts. It operates even faster than Opus.

When I ask ChatGPT or Opus to create a new feature: - ChatGPT often produces superficial results, ignoring existing code and building unnecessary independent code. - Interestingly, the outcome from ChatGPT appears functional, but it's usually incorrect, focusing on a superficial "aha!" moment.

Opus, however, plans thoroughly, executes, and cleans up, ensuring everything works correctly. If needed, I can provide more realistic examples, though it's challenging due to the monorepo's size and complexity, with hundreds of thousands of lines of code.