Cool, well let me know when Opus 4.5 level performance is available locally, at speeds that serve everyday use, and 100% I'm right there with you.

Until then, I'm going to keep sending my JSON to the server farm in Virginia because it's the only place that can serve me a model that actually works for my uses.

I experiment a lot with local models, and I agree.

I have a lot of fun with the local models and seeing what they can do.

I appreciate the SOTA models even more after my local experiments. The local models are really impressive these days, but the gap to SOTA is huge for complex tasks.

The article is not about those use cases. There are plenty of use cases for which local models are already pretty good

Reasoning over a large codebase is only one use case for large models. For the use cases in the article (summarizing, classifying, basic text rewrites) most phones can handle them just fine.

DeepSeek V4 with 1 million token context window is pretty powerful, although still not there. There's hope that Opus 4.5 level performance locally is not that far away.

Next year there will be Opus 4.5 level available on open source models so theoretically you may be able to run it locally but in reality it will be too expensive (i.e maybe 2 x max Studio 512GB ram each) for “normal” users.

Depending on a task, there are already models matching Opus 4.5. Just not in everything. But you can always swap a local model for a particular task.

The frontier Chinese open source models are already at this level, GLM-5.1 and Kimi K2.6 specifically.