用 Jev 做分类打分、Grok 只处理难请求

kocer @kocer_eth原推发布于 2026.10.10

在 X 上打开原推

you're f*cking wasting Grok on basic sorting. 1 million calls can mean $2,000 vs $42 in input costs. Grok can research a company, write code and work through a difficult problem. making it decide "sales, support or spam?" a million times deserves a different budget. here's the arithmetic for 1 million calls with 1,000 total input tokens each: › Grok 4.7 standard input: $2,000. › Jev input: $42. that's input pricing, not proof of equal accuracy or your total agent bill. Grok output, tools, retries and human review are extra. the useful move is deciding which requests need Grok before sending everything to it. take an incoming customer message: › "where's my order?" → classify the request, then query the order system. › "does this product fit my setup?" → send Grok the relevant documentation. › "refund this purchase" → check the policy and required approval before acting. › unclear intent → ask for clarification or route to review. Jev can handle narrow classification and scoring. Grok handles the work that needs deeper reasoning. your code checks permissions and controls execution. before changing your setup, collect 100 real requests and label the correct destination yourself. then check: › which requests went to the wrong place? › which mistakes could cause damage? › how often did the fallback need Grok anyway? › what did each correctly completed task cost? 100 examples are a starting test, not proof that the system is ready for every case. keep this calculation for your own workload: monthly calls × average input tokens ÷ 1,000,000 × input price. calculate output, tools and retries separately. compare standard, cached and batch rates where available. if a friend is building a Grok agent, send them the routing example before they copy the cheapest price. they need to know which jobs they can move safely, not just which number looks better.

这条是引用着另一条写的：x.com/kocer_eth/status/2092216029816472002