AI Singapore (AISG) has launched SEA-LION v4, an open-source multimodal language mannequin developed in collaboration with Google and based mostly on the Gemma 3 (27B) structure. The mannequin is designed to assist Southeast Asian languages, together with these with restricted digital sources, and offers each textual content and picture understanding capabilities. SEA-LION v4 makes use of a commercially permissive license and is meant for simple deployment on normal {hardware} platforms.
Benchmark Outcomes: “Small” however State-of-the-Artwork
Efficiency evaluations on the SEA-HELM benchmark—a rigorous multilingual suite designed particularly to check Southeast Asian (SEA) languages—verify SEA-LION v4’s capabilities. Throughout duties in Burmese, Filipino, Indonesian, Malay, Tamil, Thai, and Vietnamese, v4 achieves a prime rating amongst fashions underneath 200B parameters, and globally locations #5 out of 55 fashions examined.
This result’s putting: the mannequin is just not solely outperforming open-source friends like Llama 3, Qwen 3, and Gemma 3, but in addition holding its personal towards proprietary giants with parameter counts a number of instances bigger.
- Filipino: 74.53 (v4) vs. 74.09 (Gemma 3-27B)
- Malay: 71.31 (v4) vs. 71.20 (Gemma 3-27B)
- Tamil: 68.47 (v4) vs. 68.45 (Gemma 3-27B)
- Burmese: 57.18 (v4) simply behind Gemma 3’s 57.78, outperforming Llama 4 MoE (109B).
In lots of languages, SEA-LION v4 performs on par with or higher than fashions over 3–10x its measurement. This stability of effectivity and functionality makes it one of many strongest overtly out there multilingual fashions for each analysis and trade use.
What’s New in SEA-LION v4
The fourth-generation mannequin introduces a number of main technical developments that make it uniquely fitted to each regional and world functions:
1. Open Sourced
Not like many closed fashions, SEA-LION v4 is launched underneath the commercially permissive Gemma license, decreasing adoption boundaries for startups, researchers, and enterprises. Distribution is supported throughout a number of ecosystems:
- Hugging Face (fine-tuned and base fashions)
- Google Cloud Vertex AI
- AWS SageMaker
- Kaggle for light-weight experimentation
- NVIDIA NIM and Ollama for edge deployment
This openness ensures SEA-LION v4 will be built-in into workflows throughout each cloud-scale enterprises and on-device environments.
2. Effectivity and Portability at Scale
Regardless of its 27B parameters, SEA-LION v4 is designed to run virtually anyplace. With quantized variations in FP4 and FP8, customers can obtain:
- vs. full precision
- As much as 50% sooner inference
- Deployment on consumer-grade {hardware} (e.g., a laptop computer with 32GB RAM)
This effectivity democratizes entry: a high-quality multimodal mannequin that beforehand required in depth infrastructure is now out there to researchers or builders with modest setups.
3. Multimodality: Textual content + Imaginative and prescient
SEA-LION v4 is the initiative’s first multimodal launch. Past textual content era and understanding, the mannequin can “see,” interpret photographs, and mix multimodal data in responses. This makes it extremely related to be used circumstances similar to:
- Multilingual doc evaluation and translation with embedded photographs
- Picture-grounded query answering in native languages
- Interactive agentic workflows requiring textual content + picture context
The mannequin additionally helps 128K token context home windows, enabling prolonged reasoning over lengthy paperwork, transcripts, or multi-turn prompts, a important functionality for enterprise and analysis functions.
4. Agentic and Structured Interactions
SEA-LION v4 consists of instruments past uncooked language era, together with:
- Operate calling—enabling integration with exterior APIs and brokers
- Structured outputs—JSON and schema-compliant generations for downstream automation
- Compatibility with agentic workflows widespread in enterprise adoption of LLMs
Collectively, these enhancements lengthen SEA-LION v4 past static Q&A into real-world functions similar to workflow orchestration, analysis assistants, and multimodal enterprise bots.
Educated for Southeast Asia, Constructed for the World
A novel differentiator of SEA-LION v4 is its coaching basis. The mannequin is skilled on over 1 trillion tokens, with heavy emphasis on a curated Southeast Asian dataset. This makes it significantly sturdy in dealing with low-resource regional languages, dialects, and cultural contexts, the place world basis fashions usually fail.
In SEA-HELM’s Filipino, Malay, Tamil, and Burmese duties, SEA-LION v4 is persistently among the many best-performing fashions throughout all parameter ranges. This makes it a essential enabler for digital fairness in a area the place over 600 million individuals depend on numerous linguistic ecosystems.
On the identical time, as a result of it inherits Gemma’s sturdy general-purpose reasoning, the mannequin stays aggressive in English and world duties, making it a flexible selection for common deployment.
Conclusion
SEA-LION v4 clarify how fashions with 27B parameters, when optimized and skilled on domain-specific knowledge, can obtain aggressive leads to multilingual duties. It affords multilingual efficiency, multimodal capabilities, an open license, and deployability throughout varied platforms, contributing to developments in regional AI fashions.
Take a look at the Mannequin on Hugging Face and SEA-LION Playground. Be happy to take a look at our GitHub Web page for Tutorials, Codes and Notebooks. Additionally, be at liberty to comply with us on Twitter and don’t overlook to hitch our 100k+ ML SubReddit and Subscribe to our E-newsletter.
Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is dedicated to harnessing the potential of Synthetic Intelligence for social good. His most up-to-date endeavor is the launch of an Synthetic Intelligence Media Platform, Marktechpost, which stands out for its in-depth protection of machine studying and deep studying information that’s each technically sound and simply comprehensible by a large viewers. The platform boasts of over 2 million month-to-month views, illustrating its recognition amongst audiences.
