The models are nondeterministic, and therefore it's pretty normal for different runs to give different results.
I don't see this as evidence that Opus 4.6 has gotten worse.
And how is that an excuse?
I don't care about how good a model could be. I care about how good a model was on my run.
Consequently, my opinion on a model is going to be based around its worst performance, not its best.
As such, this qualifies as strong evidence that Opus 4.6 has gotten worse.
> And how is that an excuse? […] this qualifies as strong evidence…
This qualifies as nothing due to how random processes work, that’s what the gp is saying. The numbers are not reliable if it’s just one run.
If this is counter-intuitive, a refresher on basic statistics and probability theory may be in order.
I'm not running "statistics". I'm running an individual run. I care about the individual quality of my run and not the general quality of the "aggregate".
The problem here is that the difference may not be immediately observable. Sure, if it doesn't give a correct answer, that's quickly catchable. If it costs me 10x the time, that's not immediately catchable but no less problematic.
I see it as corroboration evidence of actual everyday experience.
Also, any reason to imply "BridgeBench", apparently dedicated to AI benchmarking, wouldn't have run it more than once across the suite?
They didn't list a sample size of runs, didn't show any numbers for variance across runs, etc...
So while they may have done that behind the scenes and just not told us, this doesn't seem like a rigorous analysis to me. It seems to me like people just want to find data that support the conclusion they already decided on (which is that Opus got worse).
https://open.substack.com/pub/sublius/p/the-semiotic-reflexi...
Come on Anthropic, admit what you're doing already and let us access your best models unhindered, even if it costs us more. At the moment we just all feel short-changed.
