It's interesting how multi-dimensional LLM capabilities have proven to be.
OpenAI reasoning models (o1-pro, o3, o3-pro) have been the strongest, in my experience, at harder problems, like finding race conditions in intricate concurrency code, yet they still lag behind even the initial sonnet 3.5 release for writing basic usable code.
The OpenAI models are kind of like CS grads who can solve complex math problems but can't write a decent React component without yadda-yadda-ing half of it, while the Anthropic models will crank out many files of decent, reasonably usable code while frequently missing subtleties and forgetting the bigger picture.
OpenAI reasoning models (o1-pro, o3, o3-pro) have been the strongest, in my experience, at harder problems, like finding race conditions in intricate concurrency code, yet they still lag behind even the initial sonnet 3.5 release for writing basic usable code.
The OpenAI models are kind of like CS grads who can solve complex math problems but can't write a decent React component without yadda-yadda-ing half of it, while the Anthropic models will crank out many files of decent, reasonably usable code while frequently missing subtleties and forgetting the bigger picture.