aisingapore/Qwen-SEA-LION-v4.5-27B-IT
Qwen-SEA-LION-v4.5-27B-IT by AI Singapore is a 27-billion parameter instruction-tuned causal language model built on the Qwen3.6 dense architecture, featuring a hybrid Linear and Full Attention design. It boasts a 262K context window and strong reasoning capabilities, with specific post-training for multilingual and multicultural fluency across English and key Southeast Asian languages including Burmese, Indonesian, Filipino, Malay, Tamil, Thai, and Vietnamese. This model excels in agentic coding, unified vision-language tasks, and retains historical reasoning context for iterative development.
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Overview
Qwen-SEA-LION-v4.5-27B-IT is a 27-billion parameter Large Language Model developed by AI Singapore, specifically designed for the Southeast Asia (SEA) region. Built upon the Qwen3.6 dense architecture, it incorporates a hybrid Linear and Full Attention design and features a substantial 262K context window. The model underwent distillation from Qwen3.5-397B-A17B using an updated aisingapore/SEA-Instruct-2602 dataset, ensuring deep domain adaptation and strong multilingual and multicultural fluency.
Key Capabilities
- Multilingual Proficiency: Fine-tuned for English and seven key Southeast Asian languages: Burmese, Indonesian, Filipino, Malay, Tamil, Thai, and Vietnamese.
- Extended Context Window: Inherits a 262K context window from Qwen3.6, enabling robust reasoning over long inputs.
- Advanced Reasoning: Designed as a highly capable reasoning model with configurable thinking modes and the ability to preserve historical reasoning context.
- Agentic Coding: Offers high-precision handling for repository-level reasoning and frontend workflows.
- Unified Vision-Language: Features early fusion training for strong performance across multimodal reasoning, coding, and visual tasks.
- Tool Calling: Demonstrates capabilities in tool use, as shown in examples for searching HDB listings and calculating mortgages.
Good For
- Applications requiring strong language understanding and generation in Southeast Asian languages.
- Tasks benefiting from a large context window, such as complex document analysis or multi-turn conversations.
- Development of agentic systems, particularly for coding and structured data interaction.
- Multimodal applications that integrate vision and language processing.
Limitations
- The model has not been aligned for safety, requiring developers to implement their own safety fine-tuning and security measures.
- It may exhibit limitations common to LLMs, such as hallucination and occasional generation of irrelevant content.