reasoning
NVIDIA Nemotron Nano 9B v2
Hybrid Mamba-transformer model for reasoning and chat with a switchable thinking budget, trained from scratch by NVIDIA.
Levelmodel
Classreasoning
Parameters8.89B
Contextnot in the notes
Released12 Aug 2025
Opennessopen weights restricted
Runs onnot in the notes
Statusactive
R&D Topics
Identity
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 Mamba-2 and transformer hybrid
- Total parameters
- 8.89B sources
- Active parameters
- –
- Checkpoint parameters
- –
- Note
- Parameter count from the safetensors index on Hugging Face.
- 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 restricted
- Licence
- NVIDIA Open Model License sources
- Access routes
- open weights download
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
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- Model card languages: en, es, fr, de, it, ja
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
DeveloperNVIDIAbig tech, USA
NVIDIAbig tech, USAModelNVIDIA Nemotron Nano 9B v2NVIDIA, reasoning
NVIDIA Nemotron Nano 9B v2NVIDIA, reasoningR&D TopicsEfficiency Architectures (MoE, Sparse Attention, Long Context)Reasoning via Large-Scale RLSmall Language Models (SLM)
Use CasesIndustrial Copilots and Maintenance AssistantsIndustrialChinese Medical LLMsHealthcareIndonesian and Regional-Language LLMsPublic SectorTelecom Domain LLMs and BenchmarksTelecomUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
PT Pertamina Geothermal EnergyIn production, 14 Jul 2026
Siemens Erlangen electronics factoryPlanned, 6 Jan 2026
ADNOC OffshoreIn production, 9 Sep 2025
Aker BPIn production, 9 Sep 2025+10 moreDeployments of these use cases; none names this model.
PT Pertamina Geothermal EnergyIn production, 14 Jul 2026Siemens Erlangen electronics factoryPlanned, 6 Jan 2026ADNOC OffshoreIn production, 9 Sep 2025Aker BPIn production, 9 Sep 2025+10 moreDeployments of these use cases; none names this model.Organisations 1
R&D topics 3
Small Language Models (SLM)Models under about 10B parameters that fit consumer devices.produced byEfficiency Architectures (MoE, Sparse Attention, Long Context)Reducing training and inference cost per capability.produced byReasoning via Large-Scale RLReinforcement learning on outcomes, often verifiable math or code, to produce long reason…produced by
Sources
- huggingface.co/nvidia/NVIDIA-Nemotron-Nano-9B-v2 https://huggingface.co/nvidia/NVIDIA-Nemotron-Nano-9B-v2
- Models at a glance - Amazon Bedrock docs.aws.amazon.com https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards.html
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "NVIDIA Nemotron Nano 9B v2", https://aurion.semai.id/models/nvidia-nemotron-nano-9b-v2/, records of October 2026.