> ## Documentation Index
> Fetch the complete documentation index at: https://docs.zerogpu.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# bge-small-en-v1.5

> Model details for bge-small-en-v1.5. 384-dimensional English retrieval embeddings with a 512-token window.

<Note>
  This model is routable only on `/v1/embeddings`. A `/responses` or
  `/chat/completions` call with an embedding model returns `400`. Send `input`
  as a string, or as an array of strings to embed a batch in one request.
</Note>

> BAAI's BGE-small-en-v1.5 is a retrieval-first English embedding model and one of the strongest performers on the MTEB benchmark for its size. Like [all-minilm-l6-v2](/api-reference/models/all-minilm-l6-v2) it produces 384-dimensional vectors, so it is a drop-in swap in an existing index, but it takes a 512-token window instead of 256 and is tuned specifically for dense retrieval rather than general sentence similarity. At 33.4M parameters it is the one to reach for when the job is ranking passages against a query: RAG retrieval, search over a document corpus, or reranking candidates before they reach a larger model.

Embeddings are priced on input tokens only. There are no output tokens to bill, so a call costs \$0.50 per 1M tokens embedded.

**References:** [Model card](https://huggingface.co/BAAI/bge-small-en-v1.5) • [License](https://opensource.org/license/mit) • [Terms](https://zerogpu.ai/terms) • [Privacy](https://zerogpu.ai/privacy-policy)


## OpenAPI

````yaml api-reference/openapi/playgrounds/bge-small-en-v1_5.openapi.json POST /embeddings
openapi: 3.1.0
info:
  title: bge-small-en-v1.5 playground
  version: '1.0'
  description: >-
    Interactive playground for **bge-small-en-v1.5**.

    Model is always `bge-small-en-v1.5` on this page (shown in the form, not
    editable).

    Authentication: `x-api-key` (required) and `x-project-id` (optional).
servers:
  - url: https://api.zerogpu.ai/v1
    description: Production
security:
  - ApiKey: []
paths:
  /embeddings:
    post:
      tags:
        - bge-small-en-v1.5
      summary: 'bge-small-en-v1.5: Embeddings'
      operationId: createEmbedding_bge-small-en-v1.5
      parameters:
        - name: x-project-id
          in: header
          required: false
          schema:
            type: string
          description: >-
            Optional project identifier. Scopes the request to a specific
            project when provided.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateEmbeddingRequest'
            examples:
              default:
                summary: Single text
                value:
                  model: bge-small-en-v1.5
                  input: >-
                    ZeroGPU runs high-volume inference tasks on small models at
                    the edge.
              batch:
                summary: Batch of texts
                value:
                  model: bge-small-en-v1.5
                  input:
                    - first text
                    - second text
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EmbeddingResponse'
              examples:
                default:
                  summary: Default
                  value:
                    object: list
                    data:
                      - object: embedding
                        index: 0
                        embedding:
                          - 0.010229
                          - 0.026804
                          - -0.00474
                          - -0.025792
                          - 0.055778
                          - 0.047825
                          - -0.044991
                          - 0.056061
                    model: bge-small-en-v1.5
                    usage:
                      prompt_tokens: 18
                      total_tokens: 18
        '400':
          description: Bad request
        '401':
          description: Unauthorized
        '403':
          description: Forbidden
        '420':
          description: Insufficient quota
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
        '500':
          description: Internal server error
components:
  schemas:
    CreateEmbeddingRequest:
      type: object
      required:
        - model
        - input
      properties:
        model:
          type: string
          const: bge-small-en-v1.5
          default: bge-small-en-v1.5
          example: bge-small-en-v1.5
          description: Model identifier (fixed for this playground).
        input:
          description: >-
            Text to embed. A single string, or an array of strings for one
            vector per element. Inputs are truncated at 512 tokens.
          oneOf:
            - type: string
              minLength: 1
              format: textarea
              maxLength: 131072
            - type: array
              minItems: 1
              items:
                type: string
                minLength: 1
    EmbeddingResponse:
      type: object
      description: >-
        An OpenAI-compatible embedding list. Vectors are truncated in this
        example; each has 384 dimensions.
      additionalProperties: true
    ErrorResponse:
      type: object
      additionalProperties: true
  securitySchemes:
    ApiKey:
      type: apiKey
      in: header
      name: x-api-key

````