2026 buyer's guide

Choosing a Korean LLM in 2026 — the independent decision guide

Independent (zero vendor funding). Public benchmarks cross-checked; figures sourced, unverified ones omitted.

TL;DR — by use case

Models at a glance

ModelVendorParamsLicensePriceKey benchmark
Solar Pro 3Upstage102B MoE (활성 12B)API$0.15/$0.6 /1MFrontier LM Intelligence 리더보드 등재 (유일 한국 모델)
HyperCLOVA X (THINK)Naver비공개 (오픈웨이트 32B Think 별도 공개)APIself-host / consoleKoBALT-700 한국어 추론 상위
EXAONE 4.0 32BLG AI Research32B (경량 1.2B 변형 존재)restrictedself-host / consoleArtificial Analysis 지능지수 62 (32B 최고)
A.X 4.0SK Telecom72B / 7B Lightopen / commercial OKself-host / consoleKMMLU 78.3 (GPT-4o 72.5 상회)
Trillion 7BTrillion Labs7Bopen / commercial OKself-host / consoleKOBEST 0.795 (한국어 벤치 최상위)
ClaudeAnthropic비공개APIself-host / console
GPTOpenAI비공개APIself-host / console
GeminiGoogle비공개APIself-host / console

License & commercial use (the gate most teams miss)

Open weights with commercial rights (A.X 4.0) let you self-host and keep data on-prem. EXAONE 4.0 ships open weights but the license restricts commercial use — verify before adopting. The rest are API-only.

Cost — list price is not the real number

Korean token efficiency moves real cost more than headline per-token price. A.X reports ~33% better Korean token efficiency than GPT-4o; for high-volume Korean workloads a Korea-tuned model can beat a cheaper-looking global model.

AI Basic Act — model choice is a compliance artifact

Effective 2026-01-22, third-party LLM adopters carry impact-assessment and record duties. Documenting why you chose a model becomes citable evidence.

By use case

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Method & limits (honest)

This guide curates publicly published benchmarks and pricing, cross-checked and labeled by source, plus independent license/cost/regulation analysis. It is not a single self-run benchmark of every model. A paid diagnostic measures your own 20 prompts.

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