Levelmodel
ClassLLM
Parameters30B
Contextnot in the notes
ReleasedDec 2025
Opennessopen source
Runs onconsumer GPU
Statusactive
Benchmark Results
maintainer-run
SEA-HELMSoutheast Asian and Indonesian
Checkpoint NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 as listed; release view (data last updated 18 Sep 2026); score is the average of 2000 bootstrapsmaintainer-run
65.36 95% CI [-1.30, +1.30]
04080
Score in score. Higher is better.
SEA-HELM leaderboard, 58 models, Indonesian (ID)
Checkpoint NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 as listed; release view (data last updated 18 Sep 2026); score is the average of 2000 bootstrapsmaintainer-run
46.89 95% CI [-0.50, +0.55]
04080
Score in score. Higher is better.
SEA-HELM leaderboard, 58 models, SEA average
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-SEA-LION-v4.8-30B-A3B is a child (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
- NVIDIA
- Family
- Nemotron 3
- Released
- Dec 2025 sourcesnotes
- 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 Hybrid Mamba MoE
- Total parameters
- 30B 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 source
- Licence
- OpenMDW License v1.1 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 (listed at 18B)
- 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
- not stated
- 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
Developer
NVIDIAbig tech, USA
NVIDIAbig tech, USAModelNemotron 3 Nano 30B-A3BNVIDIA, LLM
Nemotron 3 Nano 30B-A3BNVIDIA, LLMR&D TopicsLow-Resource and Regional Language ResourcesOpen-Weight Frontier Releases as Research SubstrateRegional 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+8 moreUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
PT Amman Mineral Nusa Tenggara (AMMAN)In production, 8 Jul 2026
PT Bank Tabungan Negara (BTN)In production, 1 Jul 2026
PT PegadaianIn production, 5 Jun 2026
Bank Central Asia (BCA)In production, 16 Mar 2026+19 moreDeployments of these use cases; none names this model.
PT Amman Mineral Nusa Tenggara (AMMAN)In production, 8 Jul 2026PT Bank Tabungan Negara (BTN)In production, 1 Jul 2026PT PegadaianIn production, 5 Jun 2026Bank Central Asia (BCA)In production, 16 Mar 2026+19 moreDeployments of these use cases; none names this model.Organisations 1
R&D topics 3
Open-Weight Frontier Releases as Research SubstrateUsing released weights as the base for downstream research.used byRegional 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…used byLow-Resource and Regional Language ResourcesDatasets, benchmarks and adaptation for under-served languages.used by
Sources
- huggingface.co/nvidia https://huggingface.co/nvidia
- huggingface.co/nvidia/models?search=nemotron-3 https://huggingface.co/nvidia/models?search=nemotron-3
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Nemotron 3 Nano 30B-A3B", https://aurion.semai.id/models/nvidia-nemotron-3-nano-30b-a3b/, records of October 2026.