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