No. OpenAI’s Batch API groups requests for asynchronous processing, but each line in the batch is still a separate request that must meet the target endpoint’s requirements. Batch jobs also have their own queue limits and completion window, so submitting many items together does not guarantee that every item will run.
What a batch does—and does not—change
An OpenAI batch input is a JSONL file with one request per line. Each line contains its own endpoint and request body, plus a unique custom_id that lets you match the result to the original request. The request body must follow the parameters accepted by that endpoint; placing it in a batch does not remove schema or endpoint requirements. OpenAI’s Batch API guide describes the line format and identifier requirement.
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Batch processing changes execution and response timing: results are returned asynchronously rather than as immediate responses to individual synchronous calls. It does not turn the file into one unrestricted request, bypass applicable policies, or guarantee that every line succeeds.
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Limits still apply to the batch
Batch has separate capacity controls, not unlimited capacity. OpenAI’s rate-limit documentation explains that batch queue limits are based on input tokens queued for a model. Pending batches count against the queue until they complete. Standard synchronous limits and batch queue limits are distinct, but each can constrain usage.
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The Batch API guide also sets batch-level limits, including maximum requests and file size, and a rate limit on batch creation. The available queued-token allowance depends on the account and model; check the current value in Platform Settings before submitting. These are operational limits, not evidence that each queued request has been exempted from its endpoint’s rules.
Check every line before submission
- Confirm endpoint and model support. Use an endpoint supported by Batch and verify that the model is available to your account. The current Batch API guide lists supported endpoints and endpoint-specific constraints.
- Validate each request body. Check every JSONL line against the endpoint’s current parameters. For example, the guide says
stream=trueis rejected for moderation requests. - Assign a unique identifier. Give each line its own
custom_idso outputs and errors can be reconciled with their inputs. - Check live capacity. Review the model-specific queued-token allowance in Platform Settings, along with batch file and request limits, before creating the job.
- Monitor the job and inspect its files. Track the batch state and review both output and error files. Treat the results as potentially partial rather than assuming every line completed.
What happens when a request fails or the batch expires?
A failed line does not make every other line successful or unsuccessful by definition. Inspect the error details for that request. A rate-limit error may call for pacing or a retry; a billing or usage-limit error may require resolving credits or an account limit. OpenAI’s rate-limit guide covers these limits, but the error itself is the important clue to which remedy applies.
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OpenAI documents a 24-hour completion window for Batch. If a batch expires, unfinished requests are cancelled; completed responses are made available, and completed work is charged. Plan for this possibility when processing jobs that cannot be treated as all-or-nothing. See the Batch API guide and Batch API FAQ for the documented completion and expiration behavior.
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Batch or synchronous requests?
| Consideration | Batch API | Synchronous calls |
|---|---|---|
| Response timing | Asynchronous; the documented completion window is 24 hours. | Returns an individual response synchronously. |
| Capacity accounting | Uses a separate queue with model-specific limits; pending jobs count against it. | Subject to standard request and token limits. |
| Request handling | One endpoint request per JSONL line, with a unique custom_id and compatible body. |
Each call must meet the endpoint’s requirements. |
| Operational outcome | Requests may fail individually, and unfinished work is cancelled at expiration. | Each call returns its own response or error. |
| Cost | Check current pricing for the relevant endpoint and model; pricing can change. | Check the same current endpoint and model pricing. |
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