[WarmWash]

People use a model as their daily driver, get very familiar with it and it's behavior, and then go and use another model and have a hard time. It's very difficult to separate "the model is bad" from "the model works differently".

[JumpCrisscross]

> It's very difficult to separate "the model is bad" from "the model works differently"

At which point it’s fair to reject the commoditization label.

Also missing from these discussions are e.g. Qwen, which is at least as good as one back from OpenAI or Anthropic’s frontiers.

[embedding-shape]

> Also missing from these discussions are e.g. Qwen, which is at least as good as one back from OpenAI or Anthropic’s frontiers.

They're missing in the discussion because the ones you can run locally, aren't actually "one step away from other closed-source labs" in practice when you use them. They might benchmark as such, but they're sadly far away from measuring up to those scores except for very specific use cases, even when you have say 96GB of VRAM available to run the bigger models even most (at home) consumers won't be able to run.

[JumpCrisscross]

> the ones you can run locally, aren't actually "one step away from other closed-source labs"

And they probably won’t be for at least another decade. Comparing like with like, flagship model running on the best hardware it can run on, Qwen is close.

[embedding-shape]

> Qwen is close

I wish so badly this was true, but sadly today it just isn't.

[JumpCrisscross]

To be clear, I’m relaying my subjective experience comparing Opus and Qwen.