Positive users find OpenAI's token efficiency dominance on the Pareto frontier interesting and important, while negative users dismiss the metric as silly since cost, latency, and actual performance like Sonnet's matter more.
Based on 12 visible X reactions from 21 accounts; directional sample.
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@ArtificialAnlys Really interesting results, more ai companies should try to score on the top, and would be even better to be at the top left. But we should also quantify how much a just need a solution that works, perhaps even without other txt response. To see which gets it right cheaper
@ArtificialAnlys Watching GPT-5.6 Sol dominate the frontier across varying effort levels highlights how critical test-time compute control really is. Giving developers a dynamic slider between speed, token count, and raw intelligence transforms agent deployment.
@ArtificialAnlys More reasoning tokens just means we’re paying for the model to "think out loud" for 30 seconds to produce code Claude gets right instantly. That’s not Pareto efficiency, that’s just glorified token inflation for our API bills.
@ArtificialAnlys Number of output tokens is a silly metric. Intelligence, latency and cost are the metrics that matter.
@ezyrider @ArtificialAnlys @GavinSBaker He meant 'Grok owns POTATO frontier...'
@ArtificialAnlys tokens? meanless $$$
Despite major launches from 5+ labs this month, OpenAI occupies most of the token efficiency Pareto frontier We measure the number of output tokens models produce per task in the Artificial Analysis Intelligence Index. Output tokens consist of answer tokens (can be thought of as how verbose the model is) and reasoning tokens (how much the model thinks before giving an answer). Reasoning tokens in particular offer a way for models to use compute at inference time to improve responses. Output tokens are an important determinant of both cost and time per task. Various effort levels of GPT-5.6 Sol dominate the frontier - Terra and Luna produce comparatively more tokens for any level of intelligence.
Positive users find OpenAI's token efficiency dominance on the Pareto frontier interesting and important, while negative users dismiss the metric as silly since cost, latency, and actual performance like Sonnet's matter more.
Based on 12 visible X reactions from 21 accounts; directional sample.
Ask a question below.
Published answers will appear here.
Compare token use and intelligence of AI models at https://artificialanalysis.ai/