Gemini 2.5 Pro vs. Claude 3.7 Sonnet: Coding Comparison

I'd like to see an honest attempt by someone to use one of these SOTA models to code an entire non-trivial app. Not a "vibe coding" flappy bird clone or minimal ioS app (call API to count calories in photo), but something real - say 10K LOC type of complexity, using best practices to give the AI all the context and guidance necessary. I'm not expecting the AI to replace the programmer - just to be a useful productivity tool when we move past demos and function writing to tackling real world projects.

It seems to me that where we are today, AI is only useful for coding for very localized tasks, and even there mostly where it's something commonplace and where the user knows enough to guide the AI when it's failing. I'm not at all convinced it's going to get much better until we have models that can actually learn (vs pre-trained) and are motivated to do so.

I've been using Claude 3.7 for various things, including helping in game development tasks. The generated code usually requires editing and it can't do autonomously more than a few functions at once but it's a fairly useful tool in terms of productivity. And the logic part is also quite good, can design out various ideas/algorithms, and suggest some optimisations.

Tech stack is nothing fancy/rare but not the usual ReactJS slop either - it's C# with OpenGL.

I can't comment about the best practices though because my codebase follows none of them.

Yes, the user has to know enough to guide the AI when it's failing. So it can't exactly replace the programmer as it is now.

It really can't do niche stuff however - like SIMD. Maybe it would be better if I compiled a cheatsheet of .NET SIMD snippets and howtos because this stuff isn't really on the internet in a coherent form at all. So it's highly unlikely that it was trained on that.