Head-to-head: Jev vs DeepSeek V4.1 Flash, instantly grasp

@NFT_Chen SuSu_酥酥👅 · Sep 19, 2026 · case #697099 · listed via Jev Hub

Still from the clip posted with this case; watch it in the original post on X.

Builder ran 500 e-commerce support tickets through Jev and DeepSeek V4.1 Flash, with Jev finishing in 83s for $0.01 versus 173 tickets for $0.06.

The original post, translated

💥 Head-to-head: Jev vs DeepSeek V4.1 Flash, instantly grasp Jev's terrifying capability! 500 real e-commerce customer service tickets, the same ticket triage task: 🔸JEV: cleared in 83 seconds, cost $0.01, the left side is already fully archived. 🔹DeepSeek: when this round was stopped, only 173 tickets were done, cost $0.06, the right side still has more than half left, about 5 times more expensive. The gap is not in "who is smarter," but in the design architecture: 🔸JEV's official positioning is

Show the original post in its source language ▾

💥实力比拼：Jev vs DeepSeek V4.1 Flash，瞬间秒懂Jev的恐怖能力！ 500条真实电商客服工单，同一套分单任务： 🔸JEV：83秒清完，花了 $0.01，左边已经全部归档。 🔹DeepSeek：这轮停单时只做完 173条，花了 $0.06，右边还剩一大半，贵了大约5倍。差距不在“谁更聪明”，在设计架构： 🔸JEV官方定位是

The post above is a machine translation from zh; the untranslated text is in the fold-out.

Engagement when collected

Views81K

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Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.

Where this case fits

Filed under classification & data extraction. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the classification & data extraction page.

🗂️ Classification & data extraction