Hunyuan Translation Model Version 1.5 includes a 1.8B translation model, HY-MT1.5-1.8B, and a 7B translation model, HY-MT1.5-7B. Both models focus on supporting mutual translation across 33 languages and incorporating 5 ethnic and dialect variations. Among them, HY-MT1.5-7B is an upgraded version of WMT25 championship model, optimized for explanatory translation and mixed-language scenarios, with newly added support for terminology intervention, contextual translation, and formatted translation. Despite having less than one-third the parameters of HY-MT1.5-7B, HY-MT1.5-1.8B delivers translation performance comparable to its larger counterpart, achieving both high speed and high quality. After quantization, the 1.8B model can be deployed on edge devices and support real-time translation scenarios, making it widely applicable.
Model Farm provides optimized model resources and test code, which can be obtained through the following two methods:
Obtain via Model Farm page: Click Models & Test Code in the Performance Reference section on the right to obtain model resources and code packages.
Obtain via command line (Recommand): Users with APLUX development boards can obtain model resources and code packages through the built-in MMS tool.
# Search Models
mms list [model name]
# Get Models
mms get -m [model name] -p [precision] -c [soc] -b [backend] -d [file path]
For MMS usage, please refer to: MMS Usage & Access to Preview Models
Key Features and Advantages
- HY-MT1.5-1.8B achieves the industry-leading performance among models of the same size, surpassing most commercial translation APIs.
- HY-MT1.5-1.8B supports deployment on edge devices and real-time translation scenarios, offering broad applicability.
- HY-MT1.5-7B, compared to its September open-source version, has been optimized for annotated and mixed-language scenarios.
- Both models support terminology intervention, contextual translation, and formatted translation.
Note: This table showed source model instead of quantized model evaluation. Source Model Evaluation refer to HY-MT1.5-1.8B Evaluation Result
Please refer to the model inference tags at the top to select an appropriate inference SDK.
Recommended to use AidGen & AidGenSE for inference