Embeddings are a numerical representation of text input that open up a number of unique use cases, such as clustering, similarity measurement and information retrieval. For an introduction, check out the Embeddings guide.

Unlike generative AI models that create new content, the Gemini Embedding model is only intended to transform the format of your input data into a numerical representation. While Google is responsible for providing an embedding model that transforms the format of your input data to the numerical-format requested, users retain full responsibility for the data they input and the resulting embeddings. By using the Gemini Embedding model you confirm that you have the necessary rights to any content that you upload. Do not generate content that infringes on others' intellectual property or privacy rights. Your use of this service is subject to our Prohibited Use Policy and Google's Terms of Service.

Method: models.embedContent

Generates a text embedding vector from the input Content using the specified Gemini Embedding model.

Endpoint

post https://generativelanguage.googleapis.com/v1beta/{model=models/*}:embedContent

Path parameters

model string

Required. The model's resource name. This serves as an ID for the Model to use.

This name should match a model name returned by the models.list method.

Format: models/{model} It takes the form models/{model}.

Request body

The request body contains data with the following structure:

Fields

Required. The content to embed. Only the parts.text fields will be counted.

Optional. Optional task type for which the embeddings will be used. Not supported on earlier models (models/embedding-001).

title string

Optional. An optional title for the text. Only applicable when TaskType is RETRIEVAL_DOCUMENT.

Note: Specifying a title for RETRIEVAL_DOCUMENT provides better quality embeddings for retrieval.

outputDimensionality integer

Optional. Optional reduced dimension for the output embedding. If set, excessive values in the output embedding are truncated from the end. Supported by newer models since 2024 only. You cannot set this value if using the earlier model (models/embedding-001).

Example request

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Go

Shell

Method: models.batchEmbedContents

Generates multiple embedding vectors from the input Content which consists of a batch of strings represented as EmbedContentRequest objects.

Endpoint

post https://generativelanguage.googleapis.com/v1beta/{model=models/*}:batchEmbedContents

Path parameters

model string

Required. The model's resource name. This serves as an ID for the Model to use.

This name should match a model name returned by the models.list method.

Format: models/{model} It takes the form models/{model}.

Request body

The request body contains data with the following structure:

Fields

Required. Embed requests for the batch. The model in each of these requests must match the model specified BatchEmbedContentsRequest.model.

Example request

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Response body

The response to a BatchEmbedContentsRequest.

If successful, the response body contains data with the following structure:

Fields

Output only. The embeddings for each request, in the same order as provided in the batch request.

Method: models.asyncBatchEmbedContent

Enqueues a batch of models.embedContent requests for batch processing. We have a models.batchEmbedContents handler in GenerativeService, but it was synchronized. So we name this one to be Async to avoid confusion.

Endpoint

post https://generativelanguage.googleapis.com/v1beta/{batch.model=models/*}:asyncBatchEmbedContent

Path parameters

batch.model string

Required. The name of the Model to use for generating the completion.

Format: models/{model}. It takes the form models/{model}.

Request body

The request body contains data with the following structure:

Fields

batch.name string

Output only. Identifier. Resource name of the batch.

Format: batches/{batchId}.

batch.displayName string

Required. The user-defined name of this batch.

Required. Input configuration of the instances on which batch processing are performed.

Output only. The output of the batch request.

batch.createTime string (Timestamp format)

Output only. The time at which the batch was created.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".

batch.endTime string (Timestamp format)

Output only. The time at which the batch processing completed.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".

batch.updateTime string (Timestamp format)

Output only. The time at which the batch was last updated.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".

Output only. Stats about the batch.

Output only. The state of the batch.

batch.priority string (int64 format)

Optional. The priority of the batch. Batches with a higher priority value will be processed before batches with a lower priority value. Negative values are allowed. Default is 0.

Response body

If successful, the response body contains an instance of Operation.

EmbedContentResponse

The response to an EmbedContentRequest.

Fields

Output only. The embedding generated from the input content.

ContentEmbedding

A list of floats representing an embedding.

Fields

values[] number

The embedding values.

JSON representation 
{
  "values": [
    number
  ]
}

TaskType

Type of task for which the embedding will be used.

Enums
TASK_TYPE_UNSPECIFIED Unset value, which will default to one of the other enum values.
RETRIEVAL_QUERY Specifies the given text is a query in a search/retrieval setting.
RETRIEVAL_DOCUMENT Specifies the given text is a document from the corpus being searched.
SEMANTIC_SIMILARITY Specifies the given text will be used for STS.
CLASSIFICATION Specifies that the given text will be classified.
CLUSTERING Specifies that the embeddings will be used for clustering.
QUESTION_ANSWERING Specifies that the given text will be used for question answering.
FACT_VERIFICATION Specifies that the given text will be used for fact verification.
CODE_RETRIEVAL_QUERY Specifies that the given text will be used for code retrieval.

EmbedContentBatch

A resource representing a batch of EmbedContent requests.

Fields

model string

Required. The name of the Model to use for generating the completion.

Format: models/{model}.

name string

Output only. Identifier. Resource name of the batch.

Format: batches/{batchId}.

displayName string

Required. The user-defined name of this batch.

Required. Input configuration of the instances on which batch processing are performed.

Output only. The output of the batch request.

Output only. The time at which the batch was created.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".

Output only. The time at which the batch processing completed.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".

Output only. The time at which the batch was last updated.

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".

Output only. Stats about the batch.

Output only. The state of the batch.

priority string (int64 format)

Optional. The priority of the batch. Batches with a higher priority value will be processed before batches with a lower priority value. Negative values are allowed. Default is 0.

JSON representation 
{
  "model": string,
  "name": string,
  "displayName": string,
  "inputConfig": {
    object (InputEmbedContentConfig)
  },
  "output": {
    object (EmbedContentBatchOutput)
  },
  "createTime": string,
  "endTime": string,
  "updateTime": string,
  "batchStats": {
    object (EmbedContentBatchStats)
  },
  "state": enum (BatchState),
  "priority": string
}

InputEmbedContentConfig

Configures the input to the batch request.

Fields
source Union type

Required. The source of the input. source can be only one of the following:

fileName string

The name of the File containing the input requests.

The requests to be processed in the batch.

InlinedEmbedContentRequests

The requests to be processed in the batch if provided as part of the batch creation request.

Fields

Required. The requests to be processed in the batch.

InlinedEmbedContentRequest

The request to be processed in the batch.

Fields

Required. The request to be processed in the batch.

metadata object (Struct format)

Optional. The metadata to be associated with the request.

EmbedContentBatchOutput

The output of a batch request. This is returned in the AsyncBatchEmbedContentResponse or the EmbedContentBatch.output field.

Fields
output Union type

The output of the batch request. output can be only one of the following:

responsesFile string

Output only. The file ID of the file containing the responses. The file will be a JSONL file with a single response per line. The responses will be EmbedContentResponse messages formatted as JSON. The responses will be written in the same order as the input requests.

Output only. The responses to the requests in the batch. Returned when the batch was built using inlined requests. The responses will be in the same order as the input requests.

InlinedEmbedContentResponses

The responses to the requests in the batch.

Fields

Output only. The responses to the requests in the batch.

InlinedEmbedContentResponse

The response to a single request in the batch.

Fields

metadata object (Struct format)

Output only. The metadata associated with the request.

output Union type

The output of the request. output can be only one of the following:

Output only. The error encountered while processing the request.

Output only. The response to the request.

JSON representation 
{
  "metadata": {
    object
  },

  // output
  "error": {
    object (Status)
  },
  "response": {
    object (EmbedContentResponse)
  }
  // Union type
}

EmbedContentBatchStats

Stats about the batch.

Fields

requestCount string (int64 format)

Output only. The number of requests in the batch.

successfulRequestCount string (int64 format)

Output only. The number of requests that were successfully processed.

failedRequestCount string (int64 format)

Output only. The number of requests that failed to be processed.

pendingRequestCount string (int64 format)

Output only. The number of requests that are still pending processing.

JSON representation 
{
  "requestCount": string,
  "successfulRequestCount": string,
  "failedRequestCount": string,
  "pendingRequestCount": string
}

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Last updated 2025-10-30 UTC.