---
title: OneJev1.6-0.8B
canonical_url: "https://www.modelscope.ai/models/OmniJev/OneJev1.6-0.8B"
md_url: "https://www.modelscope.ai/models/OmniJev/OneJev1.6-0.8B.md"
repository: OmniJev/OneJev1.6-0.8B
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/Qwen3.5-0.8B
base_model_relation: finetune
parameters: 853.0M
tensor_type:
  - BF16
library_name:
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 36
stars: 0
tags:
  - onejev
  - system-one
  - decision-model
  - calibration
  - multimodal
  - gui-agent
  - video
---

# OneJev1.6-0.8B

> OneJev1.6-0.8B - An open-source model by OmniJev on ModelScope. OneJev1.6-0.8B is the 0.8B 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/OneJev1.6-0.8B is a 853.0M-parameter image-text-to-text model on ModelScope. licensed under apache-2.0. derived from Qwen/Qwen3.5-0.8B.

- **Repository**: OmniJev/OneJev1.6-0.8B
- **License**: apache-2.0
- **Tasks**: image-text-to-text
- **Parameters**: 853.0M
- **Base model**: Qwen/Qwen3.5-0.8B
- **Tags**: onejev, system-one, decision-model, calibration, multimodal, gui-agent, video
- **Downloads**: 36
- **Stars**: 0
- **Last updated**: 2026-11-11

Source: https://www.modelscope.ai/models/OmniJev/OneJev1.6-0.8B

---

<p align="center">
  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="assets/banner-dark.svg">
    <img alt="OneJev1.6-0.8B, a Multimodal System One Decision Model" src="assets/banner.svg" width="100%">
  </picture>
</p>

<p align="center">
  <a href="https://huggingface.co/OmniJev"><img alt="Hugging Face" src="https://img.shields.io/badge/Hugging_Face-OmniJev-FFD21E?style=flat-square&logo=huggingface&logoColor=black"></a>
  <a href="https://github.com/OmniJev/OneJev"><img alt="GitHub" src="https://img.shields.io/badge/GitHub-OmniJev%2FOneJev-181717?style=flat-square&logo=github&logoColor=white"></a>
  <a href="https://omnijev.github.io/OneJev/"><img alt="Website" src="https://img.shields.io/badge/Website-OneJev-0A84FF?style=flat-square&logo=googlechrome&logoColor=white"></a>
  <a href="https://github.com/OmniJev/OneJev/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/badge/License-Apache_2.0-D22128?style=flat-square&logo=apache&logoColor=white"></a>
</p>

OneJev1.6-0.8B is the 0.8B 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 averages the weights of three full fine-tunes of [Qwen/Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B), trained on 390,000 to 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), OneJev1.6-0.8B scores 48.82, up from 42.71 for OneJev1.5-0.8B. That is the highest of any model up to 2.5B parameters on the board, and it leads its class in all five areas.

<p align="center">
  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="assets/di-class-table-dark.svg">
    <img alt="Decision Index public part, table: OneJev1.6-0.8B 48.82 against vLLM-SR d3-nano (2B) 42.22, Sieve 2B v2 37.26, vLLM-SR d3-lite (0.8B) 36.93, Crivo-150M 36.39, overall and in each of the five areas; best value in each row in magenta, second best in light pink" src="assets/di-class-table.svg" width="100%">
  </picture>
</p>

The four other models are the highest-scoring models of up to 2.5B parameters on the board.

It also scores above 47 models of 4B parameters and more on the board.

<p align="center">
  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="assets/di-larger-dark.svg">
    <img alt="Decision Index public part: OneJev1.6-0.8B 48.8 at 0.9B parameters against decisio 0.4.0 48.4, Hopper 12B 48.3, Decider 35B-A3B 47.7, JevK5 9B v0.3.3 47.6, Jebadiah 9B v2.1 47.2, JPT 9B 47.0 at 10B to 36B" src="assets/di-larger.svg" width="100%">
  </picture>
</p>

Other models' scores are their public-part scores on the board on 16 October 2026.

## Results

<p align="center">
  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="assets/results-dark.svg">
    <img alt="Results table: OneJev1.6-0.8B against Jev 1.13, Jev-Omni 12B and Qwen3.8-27B thinking; best score in each row in magenta, second best in light pink" src="assets/results.svg" width="100%">
  </picture>
</p>

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/OneJev1.6-0.8B
```

In another terminal, run this example with your own `screenshot.png`:

```bash
IMG=$(base64 -w0 screenshot.png)
curl http://localhost:8000/v1/systemone -H "Content-Type: application/json" -d @- <<EOF
{
  "state": {"task": "Pay the open invoice from ACME", "screen": "<image:1>"},
  "media": [{"type": "image", "data": "data:image/png;base64,$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