Benchmarking models across effort levels and harnesses on eval suites with real coding tasks. Because you don't need High or Max effort as much as you think.
Trying to determine how much it could cost me to benchmark Muse Wonder...every other model I have benchmarked has been able to do it no problem, in a sub.
Muse Code's $50/mo tier and can't get through even all the tasks in my benchmark suite at low effort.
Looks like I would need a budget between $310-$770 to benchmark Muse Wonder vs. $0 for models from companies like Anthropic and OpenAI since I can run those in my subs.
So...trying to think of alternate paths. I've been told that potentially Muse Code just might not be a super optimal harness, and Pi might be a better harness to use it with.
Might try this before calling it. Such a bummer because I really like the team at Meta, but I have no horse in this race and have to be independent and just let the data guide me.
And right now, I can't possibly understand why I would code with a model that is so much more expensive than the latest models from Anthropic and OpenAI.
But, not giving up yet, just can't put $500+ into benchmarking this if I already know I wouldn't recommend it for coding with the early cost-per-task data I'm seeing.
Next I'm going to compare a few tasks at low effort in Pi to see if the cost-per-task is lower than in Pi...hoping it's just the harness and not the model 🤞