Is it though? There is a reason gpt has codex variants. RL on a specific task raises the performance on that task

Post-training doesn't transfer over when a new base model arrives so anyone who adopted a task-specific LLM gets burned when a new generational advance comes out.

Resouce-affording, if you are chasing the frontier of some more niche task you redo your training regime on the new-gen LLMs