Every single model I've tested that is supposed to be anywhere near Opus, wasn't there. There is some magic sauce in Anthropic models that these benchmarks aren't demonstrating.
I think the secret sauce is about communication. It understands you and you understand it. Just a better coworker to work with. Benchmarks don’t measure that.
Opus 5.5 is flat out amazing, particularly how cheap it is in practice (I'm on a subscription and use Claude Code and I almost never even approach the cap).
I would love a benchmark suite that better reflects real-world coding performance, as having Muse Wonder in the top three makes no sense to me.
It's not just 5.5, every iteration of the frontier moving - Opus has had some edge. I'm sure it's not 100% in every scenario, I love interacting with Codex models more, but the quality of the output, in most scenarios that I've been exposed to, has been the best.
I spent the last 4 months on a mix of chatgpt and glm building some prototypes of product ideas I've had for years because claude was in the phase of obnoxious conversation and verbosity.
I took the output and original specs and handed them to Claude today and the level of insight and concise detail in it's criticism and problem solving was fantastic. Dropped the others immediately
Same. Every time I think to myself: wow, finally, this is amazing. And then I give the same thing to Opus and the bastard is always better. It's annoying to a point.
I know the log scale of that chart is valuable when surveying the full breadth of possibilities, but I would encourage people to make decisions between nearby models based on linear scaling. Linear cost is often more useful for making the actual decision.
Would you please elaborate on "really decent"? Really decent for what use exactly? I want to love it (and use it as a cheaper research model in my harness), but I really cannot get any real development done with it? It stumbles and fumbles and over-complicates, where astra just plows ahead (often in less overall time) with excellent solutions.
I really want to love this model, particularly since it's good to have an open weight model on my team so to speak, but I think I might be holding it wrong.
If you have well-defined, long running tasks that are relatively disposable but requires constant ML monitoring and overwatch e.g. web crawlers, monitoring prices, logs etc. DS4 Flash is perfect for those.
For tasks like crawling and real time log analysis etc., the costs really add up at scale.
I would love a benchmark suite that better reflects real-world coding performance, as having Muse Wonder in the top three makes no sense to me.
I took the output and original specs and handed them to Claude today and the level of insight and concise detail in it's criticism and problem solving was fantastic. Dropped the others immediately
I really want to love this model, particularly since it's good to have an open weight model on my team so to speak, but I think I might be holding it wrong.
What are you using it for?
For tasks like crawling and real time log analysis etc., the costs really add up at scale.