Local models embody the hacker spirit, constant Claude glazing is spiritually incompatible with tinkering. Don't upload your spirit to the cloud.

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.

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.

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

Opus is probably somewhere in the 5TB parameter range and needs terabytes of GPU memory.

The economics of running SOTA locally just does not make sense, because you’re not using it 24/7 at 80%+ utilization while the cloud based providers can.

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.

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.

Should be relatively quickly, 1-2 years for local models to catch up to today's SOTA.

Of course then you'll be asking "uhh lemme know when Opus 6.8 level performance is available locally". People are never happy.

Gemma 4 and Qwen 3.6 are legit beast models that would steamroll every API offering from 2 years ago.

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