LLM
Nemotron-SEA-LION-v4.8-30B-A3B
AI Singapore's Nemotron-based SEA model (base and instruct); tech report arXiv 2609.18310.
Levelmodel
ClassLLM
Parameters33B
Contextnot in the notes
Released18 Sep 2026
Opennessopen weights permissive
Runs onconsumer GPU
Statusactive
Benchmark Results
maintainer-run
SEA-HELMSoutheast Asian and Indonesian
maintainer-run
65.87 95% CI [-1.29, +1.33]
04080
Score in score. Higher is better.
SEA-HELM Indonesian, open-weight models, average of 2,000 bootstraps
maintainer-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
finetune
Nemotron 3 Nano 30B-A3B is the parent (finetune)medium confidencemodel cardWhere 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
- SEA-LION
- Released
- 18 Sep 2026 sourcesregistry date
- 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
- hybrid Mamba2-Transformer hybrid MoE
- Total parameters
- 33B sources
- Active parameters
- 3B
- 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
- open weights permissive
- Licence
- MIT License sources
- Access routes
- open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- consumer GPU
- Footprint
- Consumer GPU at NVFP4 (17B)
- 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): 65.87 (95% CI -1.29 to +1.33), run by AI Singapore (SEA-HELM leaderboard maintainer) leaderboard.sea-lion.ai
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- English + 7 SEA languages including Indonesian
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, SingaporeModelNemotron-SEA-LION-v4.8-30B-A3BAI Singapore, LLM
Nemotron-SEA-LION-v4.8-30B-A3BAI 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.Organisations 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/Nemotron-SEA-LION-v4.8-120B-A12B , Hugging Face huggingface.co https://huggingface.co/aisingapore/Nemotron-SEA-LION-v4.8-120B-A12B
- Models – Hugging Face huggingface.co https://huggingface.co/models?search=sea-lion%20v4.8
- SEA-HELM Leaderboard leaderboard.sea-lion.ai/detailed/SEA https://leaderboard.sea-lion.ai/detailed/SEA
- SEA-HELM Leaderboard leaderboard.sea-lion.ai/detailed/ID https://leaderboard.sea-lion.ai/detailed/ID
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Nemotron-SEA-LION-v4.8-30B-A3B", https://aurion.semai.id/models/ai-singapore-nemotron-sea-lion-v4-8-30b-a3b/, records of October 2026.