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

# Multilingual E5 Large Instruct API

> Multilingual E5 Large Instruct embeddings API on Venice: 1,024 dimensions, 512 input tokens, $0.013 per 1M tokens. Private, with zero data retention.

export const HubMount = ({view, children, ...props}) => {
  const [hub, setHub] = useState(null);
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<HubMount view="ModelPage" data={{"family":{"slug":"multilingual-e5-large-instruct","name":"Multilingual E5 Large Instruct","modality":"embedding","task":"embedding","provider":"microsoft","primary":"text-embedding-multilingual-e5-large-instruct","variants":["text-embedding-multilingual-e5-large-instruct"],"created":1776384000,"updated":1776384000,"privacy":["private"],"openWeights":true},"models":[{"id":"text-embedding-multilingual-e5-large-instruct","name":"Multilingual E5 Large Instruct","type":"embedding","modality":"embedding","task":"embedding","variant":"standard","provider":"microsoft","created":1776384000,"source":"https://huggingface.co/intfloat/multilingual-e5-large-instruct","privacy":"private","openWeights":true,"embedding":{"dimensions":1024,"maxInputTokens":512},"pricing":{"input":0.0125},"headline":{"value":0.0125,"unit":"per 1M tokens","basis":"input"},"endpoints":[{"id":"embeddings","method":"POST","path":"/embeddings","name":"Create embeddings","status":"stable","recommended":true}],"family":"multilingual-e5-large-instruct"}],"related":{"similar":[{"slug":"bge-en-icl","name":"BGE-EN-ICL","provider":"baai","modality":"embedding","privacy":["private"],"created":1776384000,"headline":{"value":0.0125,"unit":"per 1M tokens","basis":"input"},"variants":1},{"slug":"nemotron-embed-vl-1b-v2","name":"Nemotron Embed VL 1B v2","provider":"nvidia","modality":"embedding","privacy":["private"],"created":1776384000,"headline":{"value":0.0125,"unit":"per 1M tokens","basis":"input"},"variants":1},{"slug":"qwen3-embedding-0-6b","name":"Qwen3 Embedding 0.6B","provider":"alibaba","modality":"embedding","privacy":["private"],"created":1776384000,"headline":{"value":0.0125,"unit":"per 1M tokens","basis":"input"},"variants":1},{"slug":"qwen3-embedding-8b","name":"Qwen3 Embedding 8B","provider":"alibaba","modality":"embedding","privacy":["private"],"created":1776384000,"headline":{"value":0.0125,"unit":"per 1M tokens","basis":"input"},"variants":1}],"versions":[]},"providers":{"microsoft":{"slug":"microsoft","name":"Microsoft","logo":"/images/icons/models/text.svg"},"baai":{"slug":"baai","name":"BAAI","logo":"/images/icons/models/text.svg"},"nvidia":{"slug":"nvidia","name":"NVIDIA","logo":"/images/icons/models/nvidia.svg"},"alibaba":{"slug":"alibaba","name":"Alibaba Qwen","logo":"/images/icons/models/qwen.svg"}},"faq":[{"q":"How much does the Multilingual E5 Large Instruct API cost?","a":"$0.013 per 1M input tokens. Prices are in USD and can be paid in DIEM at parity."},{"q":"What is the Multilingual E5 Large Instruct model ID?","a":"Use `text-embedding-multilingual-e5-large-instruct` as the `model` parameter."},{"q":"Is the Multilingual E5 Large Instruct API private?","a":"Multilingual E5 Large Instruct is private: requests run on infrastructure Venice controls with zero data retention, and prompts and outputs are never stored or used for training."},{"q":"How many dimensions do Multilingual E5 Large Instruct embeddings have?","a":"1,024 dimensions, with up to 512 input tokens per item."},{"q":"Which endpoint does the Multilingual E5 Large Instruct API use?","a":"Call `POST /embeddings`."}]}} />

<div className="vx-static">
  <Accordion title="Plain-text specification">
    # Multilingual E5 Large Instruct API

    Multilingual E5 Large Instruct is an embedding model by Microsoft, available on the Venice API as `text-embedding-multilingual-e5-large-instruct`. It runs privately, with zero data retention.

    ## Multilingual E5 Large Instruct API pricing

    | Model ID | Variant | Privacy | Price |
    | - | - | - | - |
    | `text-embedding-multilingual-e5-large-instruct` | Standard | Private | \$0.01 per 1M tokens |

    ## Multilingual E5 Large Instruct specifications

    | Spec | Value |
    | - | - |
    | Provider | Microsoft |
    | Released | Apr 17, 2026 |
    | Privacy | Private |
    | Open weights | Yes |
    | Dimensions | 1,024 |
    | Max input | 512 tokens |

    ## How to use the Multilingual E5 Large Instruct API

    Send requests to `POST https://api.venice.ai/api/v1/embeddings` with `"model": "text-embedding-multilingual-e5-large-instruct"` and your API key.

    ```bash theme={null}
    curl https://api.venice.ai/api/v1/embeddings \
      -H "Authorization: Bearer $VENICE_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{
        "model": "text-embedding-multilingual-e5-large-instruct",
        "input": "Private AI for everyone."
      }'
    ```

    ## Multilingual E5 Large Instruct API FAQ

    ### How much does the Multilingual E5 Large Instruct API cost?

    \$0.013 per 1M input tokens. Prices are in USD and can be paid in DIEM at parity.

    ### What is the Multilingual E5 Large Instruct model ID?

    Use `text-embedding-multilingual-e5-large-instruct` as the `model` parameter.

    ### Is the Multilingual E5 Large Instruct API private?

    Multilingual E5 Large Instruct is private: requests run on infrastructure Venice controls with zero data retention, and prompts and outputs are never stored or used for training.

    ### How many dimensions do Multilingual E5 Large Instruct embeddings have?

    1,024 dimensions, with up to 512 input tokens per item.

    ### Which endpoint does the Multilingual E5 Large Instruct API use?

    Call `POST /embeddings`.

    ## Related models

    * [BGE-EN-ICL API](/models/bge-en-icl): \$0.01 per 1M tokens
    * [Nemotron Embed VL 1B v2 API](/models/nemotron-embed-vl-1b-v2): \$0.01 per 1M tokens
    * [Qwen3 Embedding 0.6B API](/models/qwen3-embedding-0-6b): \$0.01 per 1M tokens
    * [Qwen3 Embedding 8B API](/models/qwen3-embedding-8b): \$0.01 per 1M tokens
  </Accordion>
</div>


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