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Large Language ModelsOpen-Source AIGIGAZINE AIPublished: Sep 29, 2026, 22:00 JST

Jev-compatible Jeff hits 22ms per decision on RTX PRO 6000

Jev-compatible Jeff hits 22ms per decision on RTX PRO 6000

3 Key Points

  1. What happened

    Jeff, a small decision model packaged like Jev, comes in three versions built on Qwen3.5 0.8B, Qwen3.5 2B and Gemma 4 E2B, with a decision taking about 22 milliseconds on RTX PRO 6000 and 28 milliseconds on M4 Max.

  2. What to watch

    Jeff's README stresses it does not reason, and its backers say no model of this parameter size should be expected to handle multi-step reasoning, so its edge looks confined to fast, narrow choices.

WHO IT HITSDevelopers and product teams who want a small decision model running on their own hardware, rather than through a cloud API, are the ones this lands on, since the weights and code are openly published.

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FAQ
Is Jeff actually made by the same people as Jev?
No. The article says Jeff has no relationship with Jev's developer TypeSafe AI and has not been approved by it, though Jeff promotes compatibility with Jev. Its training code is based on the open-source AutoJev.
What is Jeff built on?
There are three versions: Qwen3.5 0.8B, Qwen3.5 2B and Gemma 4 E2B. The code is released under the MIT license and the model weights under Apache 2.0.

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