오른쪽의 플레이그라운드를 사용해 직접 테스트하십시오. Bearer sk-your-api-key를
Authorization에 넣으십시오. 기본 예시에서는 이미 심층 추론을 비활성화합니다
(thinking.disabled), 따라서 전송 시 빠른 응답을 받습니다.
이 모델은 기본적으로 많이 추론합니다 — 한 줄 질문에도 먼저 수백 개의 reasoning
token을 출력합니다. 디버깅하는 동안 예시의 "thinking": {"type": "disabled"}를 유지하십시오.
기능, 과금 및 캐싱에 대해서는
DeepSeek V4 Flash 개요를 참고하십시오.
추론이 켜져 있을 때는 max_tokens에 여유를 두십시오(추론은 출력 쿼터에 포함됩니다) — 3000+를 권장합니다
response_format는 영향을 주지 않습니다: json_schema를 전달하면 스키마를 완전히 무시한 채 200을 반환합니다. 구조화된 출력에는 tools를 사용하십시오
n는 조용히 무시됩니다: n=2를 전달하면 choices에 정확히 하나의 요소가 들어 있는 상태로 200을 반환합니다
텍스트 전용 모델 — 이미지 콘텐츠 블록을 전달하면 Model do not support image input를 반환합니다
Reasoning depth tier. Only minimal is deterministic (reasoning tokens always 0); low/medium/high/max do not form a monotonic ladder, and within-tier variance exceeds between-tier differences
Function Call tool list in standard OpenAI format. Tool arguments are genuinely constrained — use this instead of response_format when you need structured output
Usage. completion_tokens_details.reasoning_tokens is reasoning spend; prompt_tokens_details.cached_tokens is the implicit cache hit
이 페이지가 도움이 되었나요?
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