Infomaniak-AI/vllm-translategemma-27b-it
Infomaniak-AI/vllm-translategemma-27b-it is a 27 billion parameter multimodal translation model, based on Google's Gemma 3 family, optimized for deployment with vLLM. Developed by Google Translate, it excels at text and image-to-text translation across 55 languages, supporting a 32K token context length. This version features modified chat templates and RoPE configurations for enhanced vLLM compatibility, making it suitable for resource-constrained environments.
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Overview
Infomaniak-AI/vllm-translategemma-27b-it is a 27 billion parameter model derived from Google's TranslateGemma family, specifically adapted for deployment with vLLM. Developed by Google Translate, this model is designed for efficient and accurate translation tasks.
Key Capabilities
- Multimodal Translation: Capable of translating text from both text strings and images (normalized to 896x896 resolution, encoded to 256 tokens each).
- Extensive Language Support: Handles translation across 55 languages, using ISO 639-1 Alpha-2 codes or regionalized variants.
- vLLM Compatibility: Features modified chat templates to integrate language codes directly into message content, bypassing vLLM's limitations with custom content parameters. RoPE configuration has also been simplified for vLLM.
- Optimized for Resource-Limited Environments: Its relatively small size (27B parameters) allows for deployment on laptops, desktops, or private cloud infrastructure.
- High Performance: Benchmarks show strong performance on WMT24++ (MetricX 3.09, Comet 84.4) and WMT25 (MQM 5.86) for translation quality.
Good For
- Text Translation: Direct translation of text inputs between supported languages.
- Image-to-Text Translation: Extracting text from images and translating it.
- Edge Deployment: Deploying state-of-the-art translation capabilities in environments with limited computational resources.
- Developers using vLLM: Seamless integration into vLLM-based inference pipelines due to specific compatibility modifications.