multimodal LLM
Qwen-SEA-LION-v4-8B-VL
multimodal LLM from AI Singapore.
Levelmodel
Classmultimodal LLM
Parameters8B
Contextnot in the notes
Released21 Nov 2025
Opennessunknown
Runs onnot in the notes
Statusactive
Benchmark Results
maintainer-run
SEA-HELMSoutheast Asian and Indonesian
Checkpoint 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]
04080
Score in score. Higher is better.
SEA-HELM leaderboard, 58 models, Indonesian (ID)
Checkpoint 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]
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
Qwen-SEA-Guard-8B-2602 is a child (finetune)high confidencemodel card
Qwen3-VL-8B-Instruct 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, 3 models. Confidence and evidence are the notes' own.
R&D Topics
Identity
- Developer
- AI Singapore
- Family
- SEA-LION
- Released
- 21 Nov 2025 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
- not in the notes
- Total parameters
- 8B 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
- 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
- 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, SingaporeModelQwen-SEA-LION-v4-8B-VLAI Singapore, multimodal LLM
Qwen-SEA-LION-v4-8B-VLAI Singapore, multimodal LLMR&D TopicsLow-Resource and Regional Language ResourcesRegional or National Foundation Model Training (Continued Pretraining at 7B to 70B)Visual Instruction Tuning
Use CasesIndonesian and Regional-Language LLMsPublic SectorIndonesian NLU (Classification, NER)Public SectorBanking Customer Service AssistantsFinanceCitizen Service AssistantsPublic Sector+7 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 3
Organisations 1
R&D topics 3
Visual Instruction TuningConnecting a vision encoder to a language model and training it on image-grounded instruc…produced 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…produced byLow-Resource and Regional Language ResourcesDatasets, benchmarks and adaptation for under-served languages.produced by
Sources
- aisingapore/Qwen-SEA-Guard-8B-2602 , Hugging Face huggingface.co https://huggingface.co/aisingapore/Qwen-SEA-Guard-8B-2602
- huggingface.co/aisingapore/Qwen-SEA-LION-v4-8B-VL https://huggingface.co/aisingapore/Qwen-SEA-LION-v4-8B-VL
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Qwen-SEA-LION-v4-8B-VL", https://aurion.semai.id/models/ai-singapore-qwen-sea-lion-v4-8b-vl/, records of October 2026.