LLMfamily
SEA-LION
AI Singapore's SEA-LION family of Southeast Asian language models.
Levelfamily
ClassLLM
Parametersnot in the notes
Contextnot in the notes
Releasednot in the notes
Opennessunknown
Runs onnot in the notes
Statusactive
Benchmark Results
maintainer-run
SEA-HELMSoutheast Asian and Indonesian
Qwen-SEA-LION-v4.5-27B-ITmaintainer-run
76.51 95% CI [-1.23, +1.23]
rank 4, SEA-HELM Indonesian, open-weight models, average of 2,000 bootstraps
Qwen-SEA-LION-v4.5-27B-ITmaintainer-run
73.24 95% CI [-0.56, +0.57]
rank 4, SEA-HELM SEA average, open-weight models
Nemotron-SEA-LION-v4.8-120B-A12Bmaintainer-run
73.1 95% CI [-1.16, +1.21]
rank 6, SEA-HELM Indonesian, open-weight models, average of 2,000 bootstraps
Qwen-SEA-LION-v4-8B-VLCheckpoint Qwen-SEA-LION-v4-8B-VL as listed; release view (data last updated 18 Sep 2026); score is the average of 2000 bootstrapsmaintainer-run
67.21 95% CI [-1.64, +1.54]
SEA-HELM leaderboard, 58 models, Indonesian (ID)
Nemotron-SEA-LION-v4.8-30B-A3Bmaintainer-run
65.87 95% CI [-1.29, +1.33]
SEA-HELM Indonesian, open-weight models, average of 2,000 bootstraps
Gemma-SEA-LION-v4.5-E2B-ITmaintainer-run
63.96 95% CI [-1.38, +1.37]
SEA-HELM Indonesian, open-weight models, average of 2,000 bootstraps
Nemotron-SEA-LION-v4.8-120B-A12Bmaintainer-run
63.44 95% CI [-0.63, +0.61]
SEA-HELM SEA average, open-weight models
Gemma-SEA-LION-v4.5-E2B-ITmaintainer-run
59.23 95% CI [-0.66, +0.67]
SEA-HELM SEA average, open-weight models
Qwen-SEA-LION-v4-8B-VLCheckpoint Qwen-SEA-LION-v4-8B-VL as listed; release view (data last updated 18 Sep 2026); score is the average of 2000 bootstrapsmaintainer-run
56.41 95% CI [-0.79, +0.77]
SEA-HELM leaderboard, 58 models, SEA average
Nemotron-SEA-LION-v4.8-30B-A3Bmaintainer-run
51.57 95% CI [-0.52, +0.52]
04080
Score in score. Higher is better.
SEA-HELM SEA average, open-weight models
Where this comes from
Every score names who ran it: vendor-reported, maintainer-run or independent. A rank is shown with the population it was ranked in (gap rule 3).
Lineage
product of
Sahabat-AI is a child (product of)low confidencenotesSEA-LION ModernBERT 300M belongs to this familyembeddingOct 2026300MSEA-LION ModernBERT 600M belongs to this familyembeddingOct 2026600MSEA-LION ModernBERT-Embedding 300M belongs to this familyembeddingOct 2026300MSEA-LION ModernBERT-Embedding 600M belongs to this familyembeddingOct 2026600MSEA-LION-E5-Embedding-600M belongs to this familyembeddingOct 2026600MNemotron-SEA-LION-v4.8-120B-A12B belongs to this familyLLM18 Sep 2026124BNemotron-SEA-LION-v4.8-30B-A3B belongs to this familyLLM18 Sep 202633BGemma-SEA-LION-v4.5-E2B-IT belongs to this familyedge LLM19 May 20265.1BQwen-SEA-LION-v4.5-27B-IT belongs to this familyLLM19 May 202627BQwen-SEA-LION-v4-8B-VL belongs to this familymultimodal LLM21 Nov 20258BWhere this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. The tree shows two generations each way, 2 models. Confidence and evidence are the notes' own.
R&D Topics
Identity
- Developer
- AI Singapore
- Family
- not in the notes
- Released
- – sources
- Weights published
- –
- Record checked
- 10 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- not in the notes
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- text
- Output
- text
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- unknown
- Licence
- not in the notes sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- not in the notes
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- measured on a benchmark
- SEA-HELM Indonesian leaderboard (ID aggregate, first score column of the Indonesian Competency and Task Scores table): 76.51 (95% CI -1.23 to +1.23), run by AI Singapore (SEA-HELM leaderboard maintainer) leaderboard.sea-lion.ai
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Industry Use Cases
No industry use case links this model.
Links
DeveloperAI Singaporenational lab, Singapore
AI Singaporenational lab, SingaporeModelSEA-LIONAI Singapore, LLM
SEA-LIONAI Singapore, LLMR&D TopicsLow-Resource and Regional Language ResourcesRegional or National Foundation Model Training (Continued Pretraining at 7B to 70B)
Use CasesIndonesian and Regional-Language LLMsPublic SectorIndonesian NLU (Classification, NER)Public SectorBanking Customer Service AssistantsFinanceCitizen Service AssistantsPublic Sector+5 moreUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
PT Bank Tabungan Negara (BTN)In production, 1 Jul 2026
PT PegadaianIn production, 5 Jun 2026
Bank Central Asia (BCA)In production, 16 Mar 2026Bank Central Asia (BCA)In production, 16 Mar 2026+13 moreDeployments of these use cases; none names this model.
PT Bank Tabungan Negara (BTN)In production, 1 Jul 2026PT PegadaianIn production, 5 Jun 2026Bank Central Asia (BCA)In production, 16 Mar 2026Bank Central Asia (BCA)In production, 16 Mar 2026+13 moreDeployments of these use cases; none names this model.Models 11
Gemma-SEA-LION-v4.5-E2B-ITAI Singapore, edge LLMFamilySahabat-AIGoTo Gojek Tokopedia, AI Singapore, LLMProduct ofQwen-SEA-LION-v4.5-27B-ITAI Singapore, LLMFamilyQwen-SEA-LION-v4-8B-VLAI Singapore, multimodal LLMFamilySEA-LION-E5-Embedding-600MAI Singapore, embeddingFamilySEA-LION ModernBERT 300MAI Singapore, embeddingFamilySEA-LION ModernBERT 600MAI Singapore, embeddingFamilySEA-LION ModernBERT-Embedding 300MAI Singapore, embeddingFamilySEA-LION ModernBERT-Embedding 600MAI Singapore, embeddingFamilyNemotron-SEA-LION-v4.8-120B-A12BAI Singapore, LLMFamilyNemotron-SEA-LION-v4.8-30B-A3BAI Singapore, LLMFamilyOrganisations 1
R&D topics 2
Regional or National Foundation Model Training (Continued Pretraining at 7B to 70B)Pretraining or continued pretraining a mid-size model to serve a national or regional lan…produced byLow-Resource and Regional Language ResourcesDatasets, benchmarks and adaptation for under-served languages.produced by
Sources
- aisingapore (AI Singapore) huggingface.co https://huggingface.co/aisingapore
- aisingapore/Qwen-SEA-LION-v4.5-27B-IT , Hugging Face huggingface.co https://huggingface.co/aisingapore/Qwen-SEA-LION-v4.5-27B-IT
- SEA-HELM Leaderboard leaderboard.sea-lion.ai https://leaderboard.sea-lion.ai/detailed/ID
- aisingapore/Gemma-SEA-LION-v4.5-E2B-IT , Hugging Face huggingface.co https://huggingface.co/aisingapore/Gemma-SEA-LION-v4.5-E2B-IT
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "SEA-LION", https://aurion.semai.id/models/ai-singapore-sea-lion/, records of October 2026.