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AI science lab like OpenAI claim that theirso - called “ reasoning ” AI models , which can “ think ” through problems step by step , are more capable than their non - reasoning vis-a-vis in specific orbit , such as aperient . But while this loosely appear to be the vitrine , abstract thought models are also much more expensive to benchmark , making it difficult to independently verify these claims .
accord to datum from Artificial Analysis , a third - company AI examination outfit , it be $ 2,767.05 to evaluate OpenAI’so1reasoning model across a cortege of seven pop AI benchmark : MMLU - Pro , GPQA Diamond , Humanity ’s Last Exam , LiveCodeBench , SciCode , AIME 2024 , and MATH-500 .
Benchmarking Anthropic ’s recentClaude 3.7 Sonnet , a “ intercrossed ” logical thinking modelling , on the same curing of exam be $ 1,485.35 , while examine OpenAI’so3 - mini - highcost $ 344.59 , per Artificial Analysis .
Some logical thinking modelling are cheaper to benchmark than others . Artificial Analysis spent $ 141.22 measure OpenAI ’s o1 - miniskirt , for model . But on average , they be given to be pricey . All assure , Artificial Analysis has spend approximately $ 5,200 evaluate around a dozen abstract thought models , close to twice the amount the firm spent analyze over 80 non - intelligent model ( $ 2,400 ) .
OpenAI ’s non - reasoningGPT-4omodel , released in May 2024 , cost Artificial Analysis just $ 108.85 to valuate , while Claude 3.6 Sonnet — Claude 3.7 Sonnet ’s non - reasoning predecessor — be $ 81.41 .
Artificial Analysis conscientious objector - founder George Cameron told TechCrunch that the organization design to increase its benchmarking spend as more AI research lab develop reasoning models .
“ At Artificial Analysis , we melt hundreds of evaluations monthly and devote a meaning budget to these , ” Cameron say . “ We are planning for this spend to increase as models are more frequently relinquish . ”
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Artificial Analysis is n’t the only outfit of its kind that ’s dealing with develop AI benchmarking costs .
Ross Taylor , the CEO of AI startup General Reasoning , suppose he latterly spend $ 580 pass judgment Claude 3.7 Sonnet on around 3,700 unequaled prompts . Taylor estimates a single run - through of MMLU Pro , a question limit design to benchmark a manakin ’s language comprehension science , would have cost more than $ 1,800 .
“ We ’re run to a world where a lab reports x% on a benchmark where they spend y amount of compute , but where imagination for academician are < < y , ” said Taylor in arecent post on X. “ [ N]o one is going to be able to reproduce the results . ”
Why are reasoning models so expensive to test ? chiefly because they generate a mint of tokens . Tokens stage bits of raw text , such as the word “ fantastic ” split into the syllable “ sports fan , ” “ tas , ” and “ tic . ” accord to Artificial Analysis , OpenAI ’s o1 generated over 44 million tokens during the firm ’s benchmarking tests , around eight times the amount GPT-4o beget .
The immense majority of AI companies charge for model usance by the souvenir , so you may see how this cost can add up .
Modern benchmarks also tend to elicit a lot of tokens from models because they incorporate interrogation involving complex , multi - step undertaking , allot to Jean - Stanislas Denain , a older researcher at Epoch AI , which develops its own manakin benchmark .
“ [ Today ’s ] benchmarks are more complex [ even though ] the number of questions per bench mark has overall decreased , ” Denain enjoin TechCrunch . “ They often attempt to judge models ’ power to do real - world tasks , such as write and carry through code , browse the internet , and use computers . ”
Denain added that the most expensive models have get more expensiveper tokenover time . For example , Anthropic’sClaude 3 Opuswas the pricey model when it was released in May 2024 , costing $ 75 per million production tokens . OpenAI’sGPT-4.5ando1 - pro , both of which launched before this year , cost $ 150 per million yield tokens and $ 600 per million end product tokens , respectively .
“ [ S]ince model have gotten well over time , it ’s still genuine that the cost to strive a given level of operation has greatly lessen over clock time , ” Denain pronounce . “ But if you want to appraise the best largest framework at any point in sentence , you ’re still paying more . ”
Many AI laboratory , include OpenAI , give benchmarking organizations free or subsidized entree to their model for testing use . But this colors the result , some experts say — even if there ’s no evidence of manipulation , the simple suggestion of an AI laboratory ’s involvement threatens to harm the wholeness of the evaluation scoring .
“ From [ a ] scientific spot of vista , if you publish a event that no one can repeat with the same model , is it even science anymore ? ” wrote Taylor in afollow - up post on X. “ ( Was it ever science , lol ) ” .
