multimodal LLM
Intern-S2-397B
Shanghai AI Lab vision-language model; the 397B size matches Qwen3.5-397B but lineage is not confirmed.
Levelmodel
Classmultimodal LLM
Parameters403B
Contextnot in the notes
ReleasedSep 2026
Opennessunknown
Runs onmulti-GPU node
Statusactive
R&D Topics
Identity
- Developer
- Shanghai AI Lab
- Family
- not in the notes
- Released
- 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
- MoE
- Total parameters
- 403B sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- text, image
- 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
- multi-GPU node
- 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
- not in the notes
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
DeveloperShanghai AI Labnational lab, China
Shanghai AI Labnational lab, ChinaModelIntern-S2-397BShanghai AI Lab, multimodal LLM
Intern-S2-397BShanghai AI Lab, multimodal LLMR&D TopicsEfficiency Architectures (MoE, Sparse Attention, Long Context)Open-Weight Frontier Releases as Research SubstrateVisual Instruction Tuning
Use CasesClinical LLM (Open Weights)HealthcareProcess Optimisation and Advanced Process ControlIndustrialTelecom Domain LLMs and BenchmarksTelecomRobot Inspection with Instrument ReadingIndustrial+1 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 2026MIND IDResearch, 14 Oct 2025
Conch CementIn production, 23 Jun 2025
PT Kalbe Morinaga IndonesiaIn production, Oct 2024+2 moreDeployments of these use cases; none names this model.
PT Amman Mineral Nusa Tenggara (AMMAN)In production, 8 Jul 2026MIND IDResearch, 14 Oct 2025Conch CementIn production, 23 Jun 2025PT Kalbe Morinaga IndonesiaIn production, Oct 2024+2 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 byVisual Instruction TuningConnecting a vision encoder to a language model and training it on image-grounded instruc…produced byEfficiency Architectures (MoE, Sparse Attention, Long Context)Reducing training and inference cost per capability.produced by
Sources
- huggingface.co/internlm https://huggingface.co/internlm
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Intern-S2-397B", https://aurion.semai.id/models/shanghai-ai-lab-intern-s2-397b/, records of October 2026.