---
title: Confucius4-T3PO-GGUF
canonical_url: "https://www.modelscope.cn/models/netease-youdao/Confucius4-T3PO-GGUF"
md_url: "https://www.modelscope.cn/models/netease-youdao/Confucius4-T3PO-GGUF.md"
repository: netease-youdao/Confucius4-T3PO-GGUF
last_updated: 2026-09-21
license: apache-2.0
pipeline_tag: translation
tasks:
  - translation
base_model:
  - netease-youdao/Confucius4-T3PO
base_model_relation: quantized
library_name:
  - gguf
language:
  - zh
  - en
downloads: 290
stars: 4
tags:
  - gguf
  - llama.cpp
  - simultaneous-translation
  - streaming-translation
  - zh-en
  - en-zh
---

# Confucius4-T3PO-GGUF

> Confucius4-T3PO-GGUF - netease-youdao 在 ModelScope 开源的模型。Confucius4-T3PO: simulTaneous Translation via pareTo Policy Optimization

netease-youdao/Confucius4-T3PO-GGUF 是 ModelScope 魔搭社区上的translation模型，采用 apache-2.0 许可，基于 netease-youdao/Confucius4-T3PO 构建。

- **Repository**: netease-youdao/Confucius4-T3PO-GGUF
- **License**: apache-2.0
- **Tasks**: translation
- **Base model**: netease-youdao/Confucius4-T3PO
- **Tags**: gguf, llama.cpp, simultaneous-translation, streaming-translation, zh-en, en-zh
- **Downloads**: 290
- **Stars**: 4
- **Last updated**: 2026-09-21

Source: https://www.modelscope.cn/models/netease-youdao/Confucius4-T3PO-GGUF

---

<div align="center">
    <img src="./assets/logo.png" alt="Confucius4-T3PO" width="35%">
    <h1>Confucius4-T3PO: simulTaneous Translation via pareTo Policy Optimization</h1>
</div>

<div align="center">

[![Chinese README](https://img.shields.io/badge/README-中文-red)](./README-zh.md) &nbsp;&nbsp;&nbsp;&nbsp; [![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Confucius4T3PO-yellow)](https://huggingface.co/netease-youdao/Confucius4-T3PO) &nbsp;&nbsp;&nbsp;&nbsp; [![github](https://img.shields.io/badge/Github-Inference%20Code-green)](https://github.com/netease-youdao/Confucius4-T3PO)

</div>


# Confucius4-T3PO-GGUF

GGUF conversions of [`netease-youdao/Confucius4-T3PO`](https://huggingface.co/netease-youdao/Confucius4-T3PO),
a Chinese–English bidirectional streaming simultaneous translation model.
Refer to the [original model card](https://huggingface.co/netease-youdao/Confucius4-T3PO)
for the streaming protocol, the latency operating points, and evaluation results.

## Files

| File | Output type | Size |
| --- | :---: | ---: |
| `Confucius4-T3PO-F16.gguf` | `F16` | 29.5 GB |
| `Confucius4-T3PO-Q6_K.gguf` | `Q6_K` | 12.1 GB |
| `Confucius4-T3PO-Q5_K_M.gguf` | `Q5_K_M` | 10.5 GB |

The low-bit variants are quantized from the F16 GGUF. Start with `Q6_K` for a
close match to F16 quality at well under half the size; `Q5_K_M` trades a little
more quality for the smallest footprint. No GGUF splitting has been applied, so
the files run as-is. `SHA256SUMS` and `CONVERSION_INFO.md` record the checksums
and the exact conversion commands.

## Use with llama.cpp

Compile and install [llama.cpp](https://github.com/ggml-org/llama.cpp) first.

Single-shot generation:

```bash
llama-cli -m Confucius4-T3PO-Q6_K.gguf -no-cnv --temp 0 -n 128 -p "..."
```

OpenAI-compatible server:

```bash
llama-server -m Confucius4-T3PO-Q6_K.gguf --host 127.0.0.1 --port 8010
```

```bash
curl http://127.0.0.1:8010/v1/chat/completions \
  -H 'content-type: application/json' \
  -d '{
    "temperature": 0,
    "max_tokens": 128,
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "<the task prompt and the two protocol blocks>"}
    ]
  }'
```

The `user` message must follow the streaming protocol from the original model
card: the task prompt followed by the `<STREAMING_HISTORY>` and
`<CURRENT_INPUT>` blocks. An empty response means `WAIT`; a non-empty one is the
next translation segment.