---
title: Index-Translate-omni-35B
canonical_url: "https://www.modelscope.cn/models/IndexTeam/Index-Translate-omni-35B"
md_url: "https://www.modelscope.cn/models/IndexTeam/Index-Translate-omni-35B.md"
repository: IndexTeam/Index-Translate-omni-35B
last_updated: 2026-11-05
parameters: 35.8B
tensor_type:
  - BF16
  - F32
library_name:
  - safetensors
language:
  - zh
  - en
downloads: 2127
stars: 0
tags:
  - multimodal
  - translation
  - image-to-text
  - automatic-speech-recognition
---

# Index-Translate-omni-35B

> Index-Translate-omni-35B - IndexTeam 在 ModelScope 开源的模型。Index-Translate-omni 35B text, image and audio translation

- **Repository**: IndexTeam/Index-Translate-omni-35B
- **Parameters**: 35.8B
- **Tags**: multimodal, translation, image-to-text, automatic-speech-recognition
- **Downloads**: 2127
- **Stars**: 0
- **Last updated**: 2026-11-05

Source: https://www.modelscope.cn/models/IndexTeam/Index-Translate-omni-35B

---

# Index-Translate-Omni 35BA3B

Built on the Index-Translate family, with multilingual text translation, terminology and formatting constraints, image translation, speech recognition, and bidirectional Chinese–English speech translation.

## Text Translation

| Model | FLORES COMET22 ↑ | WMT24++ COMET22 ↑ | WMT26 Judge ↑ | MEME ↑ |
|---|---:|---:|---:|---:|
| Index-Translate 2B | 0.8655 | 0.8489 | 60.26 | 0.6443 |
| Index-Translate-Omni 2B | 0.8655 | 0.8489 | 60.26 | 0.6443 |
| Index-Translate 9B | 0.8789 | 0.8601 | 75.35 | 0.7387 |
| Index-Translate-Omni 9B | 0.8789 | 0.8601 | 75.35 | 0.7387 |
| Index-Translate 35BA3B (preview) | 0.8794 | 0.8586 | 76.76 | 0.7405 |
| Index-Translate-Omni 35BA3B | 0.8795 | 0.8593 | 78.01 | 0.7405 |

### Instruction Following

| Model | instTrans Quality / IFscore ↑ | instTrans_minor Quality / IFscore ↑ / Off-target ↓ | IFMTBench XCOMET-XXL / IFscore ↑ |
|---|---:|---:|---:|
| Index-Translate 2B | 0.5391 / 0.7569 | 0.3050 / 0.6586 / 3.97% | 0.7712 / 0.7584 |
| Index-Translate-Omni 2B | 0.5391 / 0.7569 | 0.3050 / 0.6586 / 3.97% | 0.7712 / 0.7584 |
| Index-Translate 9B | 0.6771 / 0.8209 | 0.5222 / 0.7725 / 3.47% | 0.7957 / 0.8760 |
| Index-Translate-Omni 9B | 0.6771 / 0.8209 | 0.5222 / 0.7725 / 3.47% | 0.7957 / 0.8760 |
| Index-Translate 35BA3B (preview) | 0.6901 / 0.8336 | 0.5151 / 0.7715 / 4.05% | 0.7926 / 0.8991 |
| Index-Translate-Omni 35BA3B | 0.6867 / 0.8371 | 0.5163 / 0.7843 / 3.62% | 0.7934 / 0.9070 |

Original Index-Translate figures come from the [published benchmarks](https://huggingface.co/IndexTeam/Index-Translate-9B#evaluation). The original 35BA3B reference is the published preview checkpoint.

## Speech

CER is a percentage (lower is better). BLEU and chrF2 are higher-is-better. Translation cells show BLEU / chrF2 / target CER.

| Model | Chinese ASR CER ↓ | English ASR CER ↓ | English → Chinese | Chinese → English |
|---|---:|---:|---:|---:|
| Index-Translate-Omni 2B | 13.8113 | 34.2560 | 36.982 / 30.357 / 43.3452 | 30.747 / 51.152 / 48.0670 |
| Index-Translate-Omni 9B | 17.8917 | 14.4097 | 43.507 / 36.312 / 41.3767 | 34.656 / 55.376 / 46.3720 |
| Index-Translate-Omni 35BA3B | 13.0053 | 15.4950 | 40.074 / 32.862 / 44.8097 | 32.411 / 53.452 / 46.1700 |

35BA3B uses one shared audio encoder and connector for all four tasks, with repetition penalty 1.1 for English ASR and the original decoding for the other tasks. Results use the same 30 fixed samples per task. One English → Chinese case reached the 256-token limit with no target translation and remains in the score. Sample counts differ across model sizes.

## Image Translation

COMET22 × 100 (higher is better). Each Omni model is compared with its Qwen3.5 baseline on paired evaluated subsets.

| Model | MMTIT ↑ | FLORES-rendered ↑ | Vistra ↑ |
|---|---:|---:|---:|
| Qwen3.5-2B | 52.164 | 50.187 | 55.326 |
| Index-Translate-Omni 2B | 65.809 | 53.612 | 65.596 |
| Qwen3.5-9B | 73.814 | 67.804 | 68.963 |
| Index-Translate-Omni 9B | 77.604 | 68.438 | 71.815 |
| Qwen3.5-35B-A3B | 75.602 | 70.005 | 71.067 |
| Index-Translate-Omni 35BA3B | 77.011 | 69.891 | 71.482 |

Image scores are retained from the evaluated image configurations and cover the evaluated subsets.

## Usage

See the [native inference guide](NATIVE_INFERENCE.md).