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API Reference

Batches

Create batch
POST/batches
Retrieve batch
GET/batches/{batch_id}
Cancel batch
POST/batches/{batch_id}/cancel
List batches
GET/batches
ModelsExpand Collapse
Batch = object { id, completion_window, created_at, 19 more }
id: string
completion_window: string

The time frame within which the batch should be processed.

created_at: number

The Unix timestamp (in seconds) for when the batch was created.

endpoint: string

The OpenAI API endpoint used by the batch.

input_file_id: string

The ID of the input file for the batch.

object: "batch"

The object type, which is always batch.

status: "validating" or "failed" or "in_progress" or 5 more

The current status of the batch.

Accepts one of the following:
"validating"
"failed"
"in_progress"
"finalizing"
"completed"
"expired"
"cancelling"
"cancelled"
cancelled_at: optional number

The Unix timestamp (in seconds) for when the batch was cancelled.

cancelling_at: optional number

The Unix timestamp (in seconds) for when the batch started cancelling.

completed_at: optional number

The Unix timestamp (in seconds) for when the batch was completed.

error_file_id: optional string

The ID of the file containing the outputs of requests with errors.

errors: optional object { data, object }
data: optional array of object { code, line, message, param }
code: optional string

An error code identifying the error type.

line: optional number

The line number of the input file where the error occurred, if applicable.

message: optional string

A human-readable message providing more details about the error.

param: optional string

The name of the parameter that caused the error, if applicable.

object: optional string

The object type, which is always list.

expired_at: optional number

The Unix timestamp (in seconds) for when the batch expired.

expires_at: optional number

The Unix timestamp (in seconds) for when the batch will expire.

failed_at: optional number

The Unix timestamp (in seconds) for when the batch failed.

finalizing_at: optional number

The Unix timestamp (in seconds) for when the batch started finalizing.

in_progress_at: optional number

The Unix timestamp (in seconds) for when the batch started processing.

metadata: optional Metadata

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

model: optional string

Model ID used to process the batch, like gpt-5-2025-08-07. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the model guide to browse and compare available models.

output_file_id: optional string

The ID of the file containing the outputs of successfully executed requests.

request_counts: optional object { completed, failed, total }

The request counts for different statuses within the batch.

completed: number

Number of requests that have been completed successfully.

failed: number

Number of requests that have failed.

total: number

Total number of requests in the batch.

usage: optional BatchUsage { input_tokens, input_tokens_details, output_tokens, 2 more }

Represents token usage details including input tokens, output tokens, a breakdown of output tokens, and the total tokens used. Only populated on batches created after September 7, 2025.

BatchUsage = object { input_tokens, input_tokens_details, output_tokens, 2 more }

Represents token usage details including input tokens, output tokens, a breakdown of output tokens, and the total tokens used. Only populated on batches created after September 7, 2025.

input_tokens: number

The number of input tokens.

input_tokens_details: object { cached_tokens }

A detailed breakdown of the input tokens.

cached_tokens: number

The number of tokens that were retrieved from the cache. More on prompt caching.

output_tokens: number

The number of output tokens.

output_tokens_details: object { reasoning_tokens }

A detailed breakdown of the output tokens.

reasoning_tokens: number

The number of reasoning tokens.

total_tokens: number

The total number of tokens used.