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Sunday, September 7, 2025

SEA-LION v4: Multimodal Language Modeling for Southeast Asia


AI Singapore (AISG) has launched SEA-LION v4, an open-source multimodal language mannequin developed in collaboration with Google and primarily based on the Gemma 3 (27B) structure. The mannequin is designed to assist Southeast Asian languages, together with these with restricted digital assets, and offers each textual content and picture understanding capabilities. SEA-LION v4 makes use of a commercially permissive license and is meant for easy deployment on normal {hardware} platforms.

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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 shouldn’t be solely outperforming open-source friends like Llama 3, Qwen 3, and Gemma 3, but additionally holding its personal in opposition to proprietary giants with parameter counts a number of occasions 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 obtainable multilingual fashions for each analysis and business use.

What’s New in SEA-LION v4

The fourth-generation mannequin introduces a number of main technical developments that make it uniquely suited to each regional and international purposes:

1. Open Sourced

Not like many closed fashions, SEA-LION v4 is launched underneath the commercially permissive Gemma license, reducing adoption limitations 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 may 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 wherever. With quantized variations in FP4 and FP8, customers can obtain:

  • <0.5% efficiency drop 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 obtainable 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 info in responses. This makes it extremely related to be used circumstances akin 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 purposes.

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 purposes akin 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 international basis fashions typically 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 various 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 international 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 gives multilingual efficiency, multimodal capabilities, an open license, and deployability throughout varied platforms, contributing to developments in regional AI fashions.


Try 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 happy to comply with us on Twitter and don’t neglect to affix 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.

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