SEA-LION v4: Multimodal Language Modeling for Southeast Asia

AI Singapore (AISG) SEA-Lion V4 has released an open source multimedand language model that was developed in cooperation with Google and is based on GEMMA 3 (27b). The model is designed to support Southeast Asian languages, including limited digital resources, and provides both the possibilities of understanding text and images. SEA-Lion V4 uses a commercial tolerant license and aims to directly publish on standard devices.

Standard results: “small” but they are modern

Performance reviews on Helm SEA standardA strict multi-language wing specially designed to test Southeast Asian languages ​​(sea)-The possibility of composing the capabilities of Sea-Lion V4. Through tasks in Burmese, Filipino, Indonesian, Malay, Tamil, Thai, and VietnameseV4 achieve a The highest classification among the models under 200B parametersGlobal Places No. 5 of 55 model have been tested.

This result is remarkable: The model does not outperform their open source peers such as Llama 3, QWEN 3 and GEMMA 3, but they also keep it against royal giants with the parameter census several times.

• Filipino: 74.53 (V4) compared to 74.09 (Gemma 3-27B)
• Malay: 71.31 (V4) compared to 71.20 (GEMMA 3-27B)
• Tamil: 68.47 (V4) compared to 68.45 (GEMMA 3-27B)
• Burme 57.18 (V4) behind Gemma 3’s 57.78, surpasses Llama 4 Moe (109B).

In many languages, SEA-Lion V4 is equal to or better than models that are more than 3 to 10 times. This balance between efficiency and ability makes it one of the strongest multi -language models available both for research and use in industry.

What is new in Sea-Lion V4

The fourth generation model offers several Main technical developments Which makes it a unique way for both regional and international applications:

1. Open a source

Unlike many closed models, SEA-Lion V4 is released below Gima license is lenient commerciallyReducing the adoption barriers of startups, researchers and institutions. Distribution is supported by multiple environmental systems:

• Embroidery (Seizing models and base)
• Google Cloud Vertex Ai
• Aws Sagemaker
• Kaggle For lightweight experiment
• Nafidia Nim and Awama To spread the edge

This openness guarantees the merging of the Sea-Lion V4 into the workflow across both cloud institutions and environments on the device.

2. Efficiency and the vibrant of pregnancy on a large scale

Despite 27B parameters, Sea-Lion V4 is designed to play practically anywhere. with Quantum versions in FP4 and FP8Users can achieve:

• <0.5 % low performance For full accuracy
• It reaches 50 % faster conclusion
• Publishing on consumer quality devices (for example, laptop computer with 32 GB RAM))

This efficiency weakens access: a high -quality multimedia model that previously requires the extensive infrastructure available for researchers or developers who have modest settings.

3. Multiple media: text + vision

SEA-Lion V4 is the initiative The first multimedia version. Beyond generating texts and understanding, the model can “see”, interpret images, and combines multimedia information in responses. This makes it a great degree related to use cases such as:

• Similar to multi -language documents and translation with compact images
• Questions on the basis of the image answer in local languages
• The agent’s interactive workflow requires a text + context of the image

The model also supports Windows of the context of the distinctive symbol 128kEnabling stretching thinking on long documents, texts or multiple claims, a decisive ability to applications and research.

4. Reactions of agents and structure

SEA-Lion V4 includes tools that go beyond raw language generation, including:

• The invitation is a jobActivating integration with applications programming and external agents
• Organized outputsJasson generations and compatibility with the plan for automation
• Compatibility with Workflow missions Popular in the adoption of the institution from LLMS

Together, these improvements on the SEA-Lion V4 extend beyond fixed questions and answers to real world applications such as coincidence of workflow, research aides, and robots of multimedia institutions.

Training on Southeast Asia, built for the world

A unique SEA-Lion V4 is a training institution. The model was trained on More than 1 trillion symbolWith a strong focus on Under the auspices of the Southeast Asian Data Group. This makes it particularly strong in dealing with low -resource regional languages, dialects and cultural contexts, as global basis models often fail.

In the Filipino tasks, Malay, Burmese and Burmese in Sea-Helm, Sea-Lion V4 is constantly among the best performance models across all parameters. This makes her a Decisive empowerment of digital shares In an area where more than 600 million people depend on various linguistic ecosystems.

At the same time, because it inherits the strong logic of general purposes, the model remains able to compete in English and international tasksWhich makes it a multi -use option for comprehensive publication.

conclusion

SEA-Lion V4 explains how 27B models can, when improving and training in the databases of the field, achieving competitive results in multi-language tasks. It provides multi -language performance, multimedia capabilities, an open license, and the ability to publish via various platforms, which contributes to progress in regional artificial intelligence models.

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Asif Razzaq is the CEO of Marktechpost Media Inc .. As a pioneer and vision engineer, ASIF is committed to harnessing the potential of artificial intelligence for social goodness. His last endeavor is to launch the artificial intelligence platform, Marktechpost, which highlights its in -depth coverage of machine learning and deep learning news, which is technically sound and can be easily understood by a wide audience. The platform is proud of more than 2 million monthly views, which shows its popularity among the masses.