> ## Documentation Index
> Fetch the complete documentation index at: https://veniceai-docs-responses-api.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 임베딩 모델

> BGE-M3, Qwen3 Embedding 등 Venice 임베딩 모델의 토큰당 가격, 프라이버시 등급, OpenAI 호환 /embeddings 사용법 안내.

<div id="model-search-placeholder" data-filter="embedding">
  API 요청에서 `id` 값을 `model` 매개변수로 사용하세요. 현재 9개의 모델을 사용할 수 있습니다.

  | Model | ID | Input (per 1M tokens) | Privacy |
  | - | - | - | - |
  | BGE-EN-ICL | `text-embedding-bge-en-icl` | \$0.01 | Private |
  | BGE-M3 | `text-embedding-bge-m3` | \$0.15 | Private |
  | Gemini Embedding 2 Preview | `gemini-embedding-2-preview` | \$0.25 | Anonymized |
  | Multilingual E5 Large Instruct | `text-embedding-multilingual-e5-large-instruct` | \$0.01 | Private |
  | Nemotron Embed VL 1B v2 | `text-embedding-nemotron-embed-vl-1b-v2` | \$0.01 | Private |
  | Qwen3 Embedding 0.6B | `text-embedding-qwen3-0-6b` | \$0.01 | Private |
  | Qwen3 Embedding 8B | `text-embedding-qwen3-8b` | \$0.01 | Private |
  | Text Embedding 3 Large | `text-embedding-3-large` | \$0.16 | Anonymized |
  | Text Embedding 3 Small | `text-embedding-3-small` | \$0.03 | Anonymized |
</div>

***

<Note>
  사용 예제는 [임베딩 API](/ko/api-reference/endpoint/embeddings/generate)를 참조하세요.
</Note>


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