Apertus-SEA-LION-v4-8B-IT

[Last update: 2026-02-05]

SEA-LION is a collection of Large Language Models (LLMs) which have been pretrained and instruct-tuned for the Southeast Asia (SEA) region.

Apertus-SEA-LION-v4-8B-IT is a 8-billion parameter model built upon the Apertus-8B-Instruct architecture. To ensure domain adaptation for the region, the model underwent rigorous post-training on a curated dataset of approximately 6.4 million instruction-text pairs.

This extensive post-training instills multilingual and multicultural fluency, covering key SEA languages such as Indonesian, Vietnamese, Thai, Filipino, Tamil, Burmese, Malay. This curated dataset also includes a filtered open sourced set of tool-calling instruction-text pairs to impart these capabilities, in addition to linguistic fluency.

Apertus-SEA-LION-v4-8B-IT is designed as a fully open model to align with this core philosophy, we have released the datasets used for post-training, as well as the evaluation codes and datasets used to evaluate the model.

These resources can be accessed via the link below.

• Open post-training datasets we used.
• SEA-HELM Evaluation codes and datasets

SEA-LION stands for Southeast Asian Languages In One Network.

We performed Post-Training in English and SEA languages on Apertus-8B-Instruct-2509, a decoder model using the Apertus architecture, to create Apertus-SEA-LION-v4-8B-IT.

For tokenization, the model employs the default tokenizer used in Apertus-8B-Instruct-2509.

• Developed by: AI Products Pillar, AI Singapore
• Funded by: Singapore NRF
• Shared by: AI Products Pillar, AI Singapore
• Model type: Decoder
• Context length: 65k
• Language(s): Indonesian, Vietnamese, Thai, Filipino, Tamil, Burmese, Malay
• License: Apache-2.0
• Finetuned from model: Apertus-8B-Instruct
• For more details, please refer to AI Singapore’s HuggingFace page for this model. The original GGUF files can be obtained from this HuggingFace repository.