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> But Cursor and other such tools depend almost entirely on accessing Anthropic, OpenAI and Gemini models, until open-source open-weight and in-house models match or exceed frontier models in quality.

I'm not sure I agree with this because even though Cursor is pay north of 100% of revenues to Athropic, Anthropic is selling inference at a loss. So if Cursor builds and hosts its own models it still has the marginal costs > marginal revenues problem.

The way out for Cursor could be a self-hosted much smaller model that focuses on code, and not the world. This could have inference costs lower than marginal revenues.



Can you have a useful code model that doesn't understand the world? It seems like such a model would be limited to little more than auto complete.


I imagine so, through distillation. Start with an all-knowing model, then extract the coding part.


they already are limited to no more than autocomplete, and they do quite badly at that too


what makes you so sure of this?

> Anthropic is selling inference at a loss.

cost of models have gone down dramatically over time.


True, but they keep using more tokens (Agentic FTW!) and the currently most expensive models.

source: https://www.wheresyoured.at/


this is not true. they use more tokens to get more performance - the cost of using the model is going up but the performance is going up with it.


Your observation does not align with recent Cursor price changes.


I’m talking about metered billing and not subscription.


cost goes down by 50% (it didn't) but you fake improvement while lacking any real improvement by taking the average of 4 runs. Cost just doubled, even though inference technically halved.

Never mind the fact that the current model is alwayj outdated, and a new (bigger one) one is always being trained in parallel with the supposedly "cheaper" inference.


I suppose supermaven is d'oing something to that effect.




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