Comment by bermudi
13 hours ago
I honestly can't believe serious people are making this argument on a straight face.
Gemini 3.7 flash outputs so many tokens per answer it doesn't matter how fast its TPS is, sol will end up being both cheaper and faster than Gemini. So ppl are paying more for a given task, waiting longer and using a dumber intelligence because "TPS number shiny".
Gemini 3.8 outputs 11k more tokens PER TASK on average in AAII than 3.7 putting it dead last in output tokens per task in the leaderboard.
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
That said, Luna is the undisputed king here at the moment and is what I use as my workhorse model.
>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.
You can limit the model viewer and they're getting better at testing multiple effort levels now: https://artificialanalysis.ai/?models=gpt-5-6-sol-medium%2Cg...
One reason is clear: Sol uses dramatically fewer output tokens than Gemini 38 flash https://artificialanalysis.ai/?models=gemini-3-8-flash%2Cgem...
It's so funny how many people diverge on the same model.
Ps. For the last week I diverged to Luna too, still need to check 3.8 flash.
But 3.6 flash was my go-to model 3 weeks ago and before it was deepseek flash/pro for a while.
None of the claude models seemed cost effective though.
AA isn't the only benchmark
https://deepswe.datacurve.ai/