By now you've probably seen Jev on your timeline.

The clip posted with this case (hosted by the collector’s media CDN); original post on X · 838s.

Benchmarked Jev against GPT-6 Astra, Fable 5.1, and Deepseek v4.1 Flash on four tasks including 1,500 emails and 857 support tickets, spending $0.49 total.

The original post

By now you've probably seen Jev on your timeline.

Yes, it's an insanely fast & cheap model.

But how does it compare against GPT-6 Astra, Fable 5.1, and Deepseek v4.1 Flash?

In this video I compare it against top LLMs on 4 distinct tasks. Did it win? Or did it lose? Let's find out.

Total Jev bill for everything in this video: $0.49.

Chapters

0:00 Intro

1:07 What Jev actually is

2:57 System 1 vs System 2 thinking

4:36 Jev plays Doom

7:14 How Jev works

10:33 Trading Bitcoin for a year

14:26 1,500 emails at 200 ms each

17:58 857 support tickets vs Intercom Fin

20:06 When you should actually use it

Engagement when collected

Views18K
Likes97
Bookmarks78
Reposts6
Replies13
Quotes4

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 video, animation & media, finance & trading, support & operations. 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 video, animation & media page.

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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post