Jev-Omni (akhilaaa3, Gemma-4-12B merged)

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akhilaaa3/jev-omni

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Jev-Omni is a typed decision model developed by akhilaaa3. It processes text inputs to return calibrated probabilities for yes/no, multiple-choice, or score questions. The model is based on a merge of the Gemma-4-12B architecture and is released as open weights.

  • decision model
  • open-weight

At a glance

providerakhilaaa3
released—
context—
input / M—

Specifications

What the API gives you

Context window
— tokens
Max output
—
Input price
— / 1M tokens
Output price
— / 1M tokens
Cache read
—
Modalities
text → decision
Knowledge cutoff
—
Released
—

Measured evidence

Public benchmark record

JevBench
67.7 ± 0.92026-10-16

LMArena data licensed CC-BY-4.0. Aider (Apache-2.0) and SWE-bench (MIT) are open. Design Arena uses blind human preference.

Open-weight model on Hugging Face.

Task evidence

How broad is the support?

Each status is exact to this model version and the selected task. Official release claims remain provisional.

  • Best Open-Weight Decision Model for Self-HostingProvisional evidence

    100% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing. 1 of 1 configured evaluation feeds currently have results.

  • Best Decision Model for Agent Routing and ScoringProvisional evidence

    100% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing. 1 of 1 configured evaluation feeds currently have results.

Recommendation coverage

Where this model appears

  1. #3Best Open-Weight Decision Model for Self-Hosting

Catalog data via OpenRouter and models.dev. Last checked within the past 6 hours.