There are numerous benchmarks that measure cost per task, which factors out tokens entirely. Gemini 3.8 flash is significantly lower than Sol on basically all of them
>There are numerous benchmarks that measure cost per task, which factors out tokens entirely. Gemini 3.8 flash is significantly lower than Sol on basically all of them
https://artificialanalysis.ai/#cost-tabs
Not sure if you read your own link but Sol 56 high ranks smack between Gemini 3.8 flash medium and high. Gemini 3.8 flash comes in as more expensive per task than Sol 56 high according to artificial analysis.
Luna high is literally 30X cheaper than Gemini 3.8 flash high.
I open the link and I see Flash 3.8 high at 0.58 and Sol at 0.95. I don't understand why you say that "Sol 56 high ranks smack between Gemini 3.8 flash medium and high" but that is clearly wrong.
On cost per intelligence task, Gemini38flash and Sol56 trade back and forth on cost depending on effort level. https://i.imgur.com/zPaWPXx.png As seen in this image, literally: Sol56 high ranks in between Gemini 38 medium and high. The image proves it.
I also included Sol56 xhigh, which ranks above even Gemini38 high.
I don't know if my code is just "complex", but I find that Luna on max ignores the surrounding style and completely ignores logical consequences of a change, like just writing `del arg1, del arg2, ...` instead of dropping it from the surrounding code. All LLMs make questionable decisions at times, but Luna requires so much guidance that it's faster to just type it out yourself. What kind of routine tasks can one accomplish with such a model?
https://artificialanalysis.ai/#cost-tabs
That said, Luna is the undisputed king here at the moment and is what I use as my workhorse model.