LG Research
1 model across 1 family · Latest: K-EXAONE 236B-A23B (2025-12)
Advancing AI for a Better Life
LG Research's portfolio covers 1 active model across 1 current family, spanning long context. Open a model detail page to compare provider routes and sourced benchmarks.
Covers 1 workload area across 1 active tracked model; last verified 2026-06-29.
Use it for
- Teams evaluating long context across this lab's releases
- Comparing model families before committing to a flagship
- Migration and pricing follow-ups across 1 tracked models
Do not use it for
- Choosing a hosting provider without opening a model page for price ladders
Active models
1
Current models from this lab, excluding deprecated ones
Active families
1
Current model families from this lab
Open catalog
1 open
0 open source / 1 open weights
Lowest output price
Not tracked
No provider output pricing linked yet
Latest dated release
2025-12-31
K-EXAONE 236B-A23B
Freshness
2026-06-29
Researched 19d ago
Information
Release cadence
Showing 1 recent dated release (full timeline below). Latest: K-EXAONE 236B-A23B (2025-12-31).
Where this lab wins
- Long-context: 1 tracked model with context-token or InfiniteBench-class signal.
Flagship quality / price signal
Flagship: K-EXAONE 236B-A23B (best sourced coding quality-per-dollar in this portfolio).
Quality-per-dollar unavailable for this flagship — benchmark coverage or output token pricing is still missing.
LG Research is a South Korean AI research organization founded in 2020. Advancing AI for a Better Life. LG Research ships 1 model family totaling 1 model, with the most recent release K-EXAONE 236B-A23B in 2025-12. Notable families include K-EXAONE. Use it as a stable reference for lab background, release coverage, and follow-up model pages as they are added. Researchers and evaluators. View official API endpoints, benchmark performance, and coding/agent fit for every LG Research model.
About
LG AI Research, established in 2020 in South Korea, is an AI think tank focused on securing AI source technologies and tackling complex AI problems. Their mission extends beyond technological advancement, aiming to create tangible value for customers through strategic partnerships with institutions like the University of Toronto and Google Cloud. They also collaborate with UNESCO to promote ethical AI development. The organization's key AI technology is the EXAONE generative AI model series. This includes EXAONE 3.0, a bilingual model; EXAONE 3.5, with improved performance models; and EXAONE Deep, which excels in reasoning AI. LG AI Research also explores deep reinforcement learning, 3D scene understanding, Explainable AI, and continual learning, with applications in industrial anomaly detection and biomedical research. LG AI Research has achieved top rankings in machine learning competitions like KorQUAD 2.0 and Stanford SQuAD. Their AI artist, Tilda, gained recognition at New York Fashion Week, and their Atelier technology received the Digital Future Innovation Award. The company focuses on developing efficient AI models for local processing, demonstrating a commitment to practical application.
Featured models
| Model | Released | Context | Input price ($/1M) | Output price ($/1M) | License | Openness |
|---|---|---|---|---|---|---|
| K-EXAONE 236B-A23B | 2025-12-31 | 256k | - | - | Open Weights | Open weights |
Model families
Recent releases
- K-EXAONE 236B-A23B- 2025-12-31
FAQ
Who founded LG Research and when?
LG Research was founded in 2020 and is associated with South Korea.
What models has LG Research released?
LG Research ships 1 model across 1 family: K-EXAONE.
Is LG Research's technology open source?
All tracked models are released under Open Weights.
Where is LG Research headquartered?
LG Research is headquartered in South Korea.
What is LG Research known for?
Advancing AI for a Better Life. Its most prominent tracked family is K-EXAONE.
How can I access LG Research's models?
LG Research's provider availability is tracked on model pages as API and hosting data is verified.
Explore related pages
Last reviewed: 2026-06-29. Data sourced from public lab announcements and provider documentation.