i use open weight models all the time, whenever a noteable one drops i will use it for the day, they are not even close for involved work.
you are definitely displaying strong bias that Anthropic is way ahead of everyone throughout your posts under this story
as such, I give your opinions zero weight, they don't align with the majority of accountings or my own experiences
here's an example of Qwen-3.6 35B A3B MoE porting my phd code to JAX with only high level guidance from my expertise, newer qwen models share the same noticeable step change in capability as recent Big Ai models
https://github.com/verdverm/pge-jax#note-from-author
are open weights lagging, yes, are they way behind, no
if open weights were so inferior, they would not be >50% of all token processing
I don't think this follows at all. Just like benchmarks get saturated, lots of tasks get saturated as well. Over time, you can accomplish a given task for much cheaper, and part of that is due to open weight models. That doesn't imply that they're competitive with frontier models for the most advanced tasks, which might represent a smaller fraction of overall work, and thus use a smaller portion of tokens.
That said, at the moment I'm finding that not much can compete with GPT-6 Luna on cost / performance (not using for coding, but for AI pipelines in my product).
this is different and nuanced from the "not even close" or "they are trash" that the other person in this thread has opined, note how they also claim Claude is way ahead of OAI as well
why are open weight models seeing such rapid rise in usage?
there has been a step function change this summer, like the end of last year for closed models
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do you think you would experience real (legitimate) feelings of loss were you not able to chat with Claude again?
(for clarity, I am not attempting to delegitimize real feelings that real people experience, regardless of my biases, it's a question from curiosity about how others are engaging with the technology)