Starting candidate
Solar Pro 3
Balances Korean consistency and cost for high-volume support.
Upstage128K context
Evidence source ↗Decide which Korean LLM to deploy — with an independent evaluation.
KoreanLLM evaluates Korean LLMs with zero vendor funding. A free model-fit diagnostic narrows your shortlist; a paid diagnostic verifies cost, contamination, and Korean quality and delivers an adoption decision plus AI-Act-ready evidence in one page.
■ Zero vendor funding
■ Contamination-audited
■ AI-Act citable evidence
■ Public eval datasets · DOI
3-minute free shortlist
Choose the use case and KoreanLLM narrows it to two candidates, why they are here, and what to verify next using public sources and editorial rules.
Checking this browser for a previous diagnostic.
Free starting shortlist
Solar Pro 3 / HyperCLOVA X (THINK)
This is a starting point narrowed from public information, not a measured score or a winner on your prompts.
Selection basis
Matches the sourced editorial recommendation on Best Korean LLM for customer support chatbots
Comparison candidate
HyperCLOVA X (THINK)
A comparison candidate for the same criteria: Honorific consistency, refusal balance, and cost are key. Strong Korean reasoning/search (high on Korean benchmarks); tight Korean data/search integration.
Naver128K context
Evidence source ↗Verify next
- 1Measure both candidates on the same 20 work prompts and explicit pass/fail criteria
- 2Use anonymized samples before an NDA and check data-retention settings first
- 3Collect tokens, retries, and p95 latency from pilot call logs
- 4Use a blind gold-set review prioritizing honorifics, refusals, omissions, and evidence accuracy
Recommended package
48h Diagnostic
₩490,000
We deliver 20 real work prompts, failure samples, cost scenarios, and vendor questions.
Report output
- ✓Measured table under identical prompts
- ✓Failure/hallucination cases
- ✓Estimated monthly cost
- ✓Buy/wait decision
Buying brief
KoreanLLM buying brief Use case: Support Data: Internal docs Volume: 100K calls/mo Priority: Quality first Candidate A: Solar Pro 3 Candidate B: HyperCLOVA X (THINK) Selection basis: Matches the sourced editorial recommendation on Best Korean LLM for customer support chatbots Not measured: performance on your own prompts Verify next: Measure both candidates on the same 20 work prompts and explicit pass/fail criteria Recommended package: 48h Diagnostic / ₩490,000
Request a Korean LLM evaluation
Pick a package, timeline, and buyer type and a payment or invoice request is built instantly. If a checkout link is connected the button opens payment; otherwise it prepares an invoice / card-link request. Enterprise buyers can copy the PO text into internal approval tools.
Invoice / card-link request
KoreanLLM evaluation request Package: 48h Diagnostic Price: ₩490,000 Timeline: Can pay today Buyer type: Startup / team lead Company/team: Contact: Preferred delivery date: Invoice/card-link recipient:
Paid diagnostic offers
48h Diagnostic
₩490,000
A fast pre-buy decision. We compare 5 candidate models on your 20 Korean work prompts and deliver cost, Korean failure patterns, and a buy/wait conclusion in one page within 48 hours.
- ✓Model shortlist
- ✓5 Korean failure patterns
- ✓Monthly cost estimate
- ✓Buy/wait conclusion
7d Benchmark Sprint
₩1,900,000
Replaces an internal PoC: a real work-prompt suite, per-use-case scorecard, and an executive memo deciding which model goes where.
- ✓Use-case scorecard
- ✓Prompt suite
- ✓Cost/latency table
- ✓Adoption roadmap
Enterprise Evaluation
₩7,500,000+
For regulated teams (finance, public sector): vendor comparison, security review, an AI-Act impact-assessment evidence table, and an executive report.
- ✓Private prompt suite
- ✓AI-Act evidence table
- ✓Executive report
- ✓Quarterly re-eval option
Compare Korean LLMs
★ 2026 Korean LLM decision guide
Read →Independent, sourced, by use case — the full guide
From request to decision in 48h
1
Collect use case
No raw documents required. Start with purpose, tone, and failure criteria.
2
Independent evaluation
Self-run license-clean benchmarks plus cross-checked public scores measure Korean instruction-following, cost, and hallucination.
3
Deliver decision
Which model to buy, which to drop, and the compliance evidence — in 48 hours.
Public proof assets
Failures & Cost2026-05-29
429 rate limit이 멈춘 6분 — 모델보다 인프라가 먼저 죽는다는 신호
결론부터. 한 에이전트 세션이 워크스페이스 구조를 분석하려다 시작 6분 만에 죽었다. 모델이 답을 못 한 게 아니라, 요청 한도가 먼저 마감됐다. 누적 실패 11,147건의 분포가 그 자리를 정확히 가리킨다.
11,147실패 누적 (7,729 세션 / 132,293 이벤트)
Fast evidence pages
Existing research and notes stay as trust evidence
Latest notes
In Practice2026-05-26
에이전트를 만드는 날, 손은 셸만 두드렸다
그날 열린 세션은 74개, 주고받은 메시지는 32,209건, 실행한 도구는 12,878회였다. 그런데 그 12,878회 중 6,382회가 단 하나의 도구 — 셸 명령이었다. 도구 호출의 절반이 같은 손짓이었다. 무엇을 그렇게 많이 두드렸나.
74그날의 핵심 수치
Tooling2026-05-25
26개의 손, 그러나 한 손이 1,333번을 주고받은 날
그날 열린 세션은 단 26개였다. 직전에 95개의 손이 한 책상을 나눠 쓰던 날과 비교하면 1/4도 안 됐다. 그런데 그 26개의 손이 주고받은 메시지는 34,654건, 실행한 도구는 20,444회였다. 손이 적어진 게 아니라, 각자 더 깊이 내려간 날이었다.
26그날의 핵심 수치
Patterns2026-05-24
기능이 아니라 '배관'을 만든 248번의 세션
프롬프트는 495개였다. 그런데 그 안에서 기계가 움직인 횟수는 42,191회. 한 줄 명령마다 도구가 평균 85번 돌았다는 뜻이다. 그 248번의 세션 동안 만든 건 화면에 보이는 기능이 아니었다. 보이지 않는 배관이었다.
248그날의 핵심 수치
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