A multimodal decision classifier for text, images, audio and video. Supply a question and options; receive a probability for each option—not a generated explanation. Built on Gemma 4 12B IT, with a 30,000-question fine-tuning run. Merged-model results. ¹Equal-weight scenario/group average. Reference scores are officially reported by their developers and may use different evaluation protocols. Jev-Omni cost uses its recorded input tokens at OpenRouter's Gemma 3 12B input rate ($0.05/M); its classifier generates no output tokens. Both classifiers are priced one call per question: a classifier answers one question at a time, so the state is re-sent for each of them and there is no discount for…
Independent publisher
Wiktor Ryznar
Rydward98
Models in Library1
Datasets in Library0
Models on Hugging Face1
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Published tasks: Text classification.
Reported licenses: apache-2.0. Open a record to review its specific license and conditions.
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