Can you really replace paid models with a local model?

Long time lurker, and I say this as someone who genuinely loves this community and runs many local models myself. I’ve been using LLMs since the early GPT and LLaMA days. Obviously, models have come a unbelievably long way. Local/open models today are dramatically better than what we had a even a few months ago. But I also think the community has developed a strange habit of wildly overstating how close these models are to frontier closed models. We now have very large open models from DeepSeek, MiniMax, GLM, Kimi, MiMo, blah blah that almost nobody can run at home. Then there are the accessible mid sized models, flash variants, and increasingly capable smaller models. And every weeks there’s another thread saying some 27B Qwen model 'replaced Claude' or is 'basically SOTA at home.' I don’t think that is even *close* to true. These models are useful. Some of them are genuinely really impressive for their size. Some are genuinely excellent for local tool calling, extraction, summarisation, private data tasks and specific finetunes. But compared to frontier closed models for serious agentic work, they are still generations behind. Obviously benchmarks lie, but they still make it look like a 27B dense model or 200B MoE is somehow in the same conversation as a multi trillion parameter frontier model. But you actually try to use it in a real coding harness, or on a big repo, or for a multi step task where the model has to infer intent, maintain context, patch its own mistakes, and make judgment calls. That’s when it falls flat. A task that takes a frontier model a few minutes and a couple of patches can take a local model a frustrating amount of steering, retries, corrections, and babysitting. Long horizon complex tasks are where these models really struggle. So question, do you truly believe any local model can replace a frontier model for serious agentic work, or is everyone mostly just here for the privacy and tinkering (or just rp)?