---
title: OneJev1.6-4B
canonical_url: "https://www.modelscope.ai/models/OmniJev/OneJev1.6-4B"
md_url: "https://www.modelscope.ai/models/OmniJev/OneJev1.6-4B.md"
repository: OmniJev/OneJev1.6-4B
last_updated: 2026-11-11
license: apache-2.0
pipeline_tag: image-text-to-text
tasks:
- image-text-to-text
model_type:
- qwen3_5
architectures:
- Qwen3_5ForConditionalGeneration
base_model:
- Qwen/Qwen3.5-4B
base_model_relation: finetune
parameters: 4.5B
tensor_type:
- BF16
library_name:
- safetensors
- pytorch
frameworks:
- pytorch
downloads: 39
stars: 0
tags:
- onejev
- system-one
- decision-model
- calibration
- multimodal
- gui-agent
- video
---
# OneJev1.6-4B
> OneJev1.6-4B - An open-source model by OmniJev on ModelScope. OneJev1.6-4B is the 4B model of OneJev 1.6, a multimodal System One decision model. Give it a screenshot, a photo, a video or plain text along with a few typed questions, and it returns a…
OmniJev/OneJev1.6-4B is a 4.5B-parameter image-text-to-text model on ModelScope. licensed under apache-2.0. derived from Qwen/Qwen3.5-4B.
- **Repository**: OmniJev/OneJev1.6-4B
- **License**: apache-2.0
- **Tasks**: image-text-to-text
- **Parameters**: 4.5B
- **Base model**: Qwen/Qwen3.5-4B
- **Tags**: onejev, system-one, decision-model, calibration, multimodal, gui-agent, video
- **Downloads**: 39
- **Stars**: 0
- **Last updated**: 2026-11-11
Source: https://www.modelscope.ai/models/OmniJev/OneJev1.6-4B
---
OneJev1.6-4B is the 4B model of OneJev 1.6, a multimodal System One decision model. Give it a screenshot, a photo, a video or plain text along with a few typed questions, and it returns a calibrated probability for every option in a single forward pass. It is a full fine-tune of [Qwen/Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B) on about 440,000 questions drawn from real agent runs, videos, images and the training splits of public decision datasets.
## Decision Index
On the public part of [Decision Index 0.3](https://huggingface.co/spaces/multimodalart/jev-decision-index) (37 benchmarks, 140,178 requests, run and scored with the board's own kit), OneJev1.6-4B scores 62.01, up from 54.89 for OneJev1.5-4B. Every model on the board that scores higher has 25B parameters or more. It has the best score in four of the five areas among the five models below, and the second best in Language Understanding.
The four other models are the highest-scoring models of 3B to 6B parameters on the board.
It also scores above 42 of the 57 models of 25B to 36B parameters on the board.
Other models' scores are their public-part scores on the board on 16 October 2026.
## Results
Accuracy in percent. The OneJev test set holds questions of the training kinds that no model saw in training. Jev 1.13's scores are its published ones, and it reads text only.
## Quick start
```bash
uv venv -p 3.12 && source .venv/bin/activate
uv pip install flide torchvision
flide serve --model OmniJev/OneJev1.6-4B
```
In another terminal, run this example with your own `screenshot.png`:
```bash
IMG=$(base64 -w0 screenshot.png)
curl http://localhost:8000/v1/systemone -H "Content-Type: application/json" -d @- <"},
"media": [{"type": "image", "data": "data:image/png;base64,$IMG"}],
"questions": {
"done": {"type": "noul", "instructions": "The invoice has been paid"},
"next": {"type": "choice", "instructions": "What should the agent do next?",
"criteria": {"click": "click an element", "type": "type text", "scroll": "scroll", "stop": "stop"}},
"progress": {"type": "score", "instructions": "How far along is the task?",
"criteria": ["not started", "halfway", "almost done", "done"]}
}
}
EOF
```
`answers.done.noul` is the probability of yes, `answers.next.probabilities` gives one probability per option and `answers.progress.score` is the expected level.
[Flide](https://github.com/OmniJev/Flide) ([paper](https://arxiv.org/abs/2610.42148)) serves TypeSafe's System One API plus a `media` field for images and video. More examples are on [GitHub](https://github.com/OmniJev/OneJev).
## Citation
```bibtex
@misc{onejev2026,
title = {{OneJev}: A Multimodal System One Decision Model},
author = {{OmniJev Team}},
year = {2026},
howpublished = {\url{https://github.com/OmniJev/OneJev}}
}
```
## License
Apache 2.0
