If you're primarily writing code yourself or meticulously reviewing the output from agents, then you're right. However, if you tried to have any of those models one-shot an app or do some highly agentic work, they would certainly fail. That's the future people are looking towards with these valuations: when its no longer economical for humans to write or even understand code, just let the models drive because they are superhuman at it. Not saying we are there today, but that's when you really start to see the benefit of more expensive models. Luna or Deepseek flash would never find any of the mathematical discoveries or security exploits that the larger models can find.

Claude is certainly able to make a superhuman mess. All of its efficacy still hinges upon good architecture and programming principles, which do not seem to be instilled in the model by anything other than luck

I'm not convinced that one-shotting things is anything other than a vanity-metric.

Maybe in the distant future where quickly building a visualisation to help explain some concept would be valuable to one shot quickly - but "One shotting an app" is ridiculous because app development (or any development) is never "build it and then finish" but is an interative process, testing feedback, user feedback, and even app-creator communication ambiguity means being able to "one shot an app" is pretty worthless

I've been using GLM 5.3 for the past week, and I find to does a straight up better job than Opus 5 on my projects. I use both for agentic work, and GLM tends to dig deeper into tasks on the latest version.

But.. what is it that anthropic does that cannot be replicated by open models teamed up with open source? Heck open source even has cheap AI to help write the code now.