Source: https://ailoot.ai/models/en/openai-gpt-4o-u003a-batch/
Canonical: https://ailoot.ai/models/en/openai-gpt-4o-u003a-batch/
Language: en

# OpenAI: GPT-4o (batch)

[Markdown](https://ailoot.ai/models/en/openai-gpt-4o-u003a-batch/index.md) · [JSON](https://ailoot.ai/models/en/openai-gpt-4o-u003a-batch/facts.json)

## [OpenAI: GPT-4o (batch)](https://ailoot.ai/models/en/openai-gpt-4o-u003a-batch/)

GPT-4o combines text and image understanding with writing, coding, Structured Outputs and application tools. Use it to develop an evidence-based response, interpret visual material or return defined fields from a substantial source collection.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-4o:batch`](https://ailoot.ai/models/en/openai-gpt-4o-u003a-batch/#method-0)

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

GPT-4o is OpenAI’s versatile GPT model for text and image understanding, writing and application work. The “o” stands for “omni”, while this documented model accepts text and images and returns text, including Structured Outputs. A practical request can combine a written brief with photographs, screenshots or document pages and ask for a clear explanation, an edited artifact or defined fields for another application stage.

For a report, provide the source documents and the decision the report should support. Identify the relevant dates, units and evidence labels, then request a comparison that separates observations, assumptions and missing information. For a visual task, point to the object, chart or interface state that matters and include the surrounding context. For a code change, supply the affected code, the desired behavior and the constraints that must remain intact. These are concrete ways to use the model’s text and image capabilities without relying on the prompt to imply the whole task.

OpenAI’s current GPT-4o profile lists a 128,000-token context window, a maximum output of 16,384 tokens and a knowledge cutoff of October 1, 2023. The producer lists several dated GPT-4o snapshots separately. The conversation, input material and generated answer share the context budget, so a large document collection still needs organisation and room for its final artifact. Facts that change or come from a private system should be supplied directly or obtained through an explicitly configured tool.

The vision guide accepts PNG, JPEG, WebP and non-animated GIF. GPT-4o supports low, high and auto image detail; high and auto follow tile-based processing. Enlarge small labels, keep text upright and preserve the legend or surrounding diagram when interpreting a chart. The documented limitations include precise spatial localisation, approximate object counts, some non-Latin writing and panoramic or fisheye views. The model can also describe an image incorrectly, so retain the source and ask for the specific observations that support an interpretation. In OpenAI’s documented vision workflow, the total request payload is limited to 512 MB and a request can include up to 1,500 images; the images and text must also fit the model’s context.

OpenAI’s file-input workflow gives a vision-capable model both extracted text and page images from PDFs. Non-PDF office documents supply extracted text rather than their embedded charts, and spreadsheets are augmented from up to the first 1,000 rows per sheet. Each file must be under 50 MB, with 50 MB combined across a request. Chat Completions supports PDF file parts; the documented Responses workflow accepts additional file formats. Choose a PDF representation where visual fidelity matters and keep source identifiers visible in the result.

Streaming can return the response as it is generated. Structured Outputs constrains a completed response to the supported subset of JSON Schema, making it useful for document extraction or an application object with defined fields. JSON mode only addresses JSON validity. Define the expected types, allowed values and treatment of absent evidence, then handle explicit refusals or incomplete responses separately. A schema does not establish whether a value is factually correct, so the requested fields should remain traceable to the supplied material.

The producer supports function calling, web search, file search, code interpretation and MCP connections. Custom functions need meaningful descriptions and argument schemas; the application executes the requested action and returns its result for the next model step. GPT-4o can also direct a separate image-generation tool in a configured Responses workflow. A tool-created image is its own artifact, while GPT-4o’s native documented response is text. An agent’s final explanation should use actual retrieved or calculated observations rather than treating a proposed tool call as a completed operation.

Predicted Outputs is available for GPT-4o when regenerating largely known text or code with small changes. Supply the existing content and a precise modification, then inspect the returned artifact. This text-only path does not combine with function calling and excludes logprobs, max\_completion\_tokens and several other controls. A tool-based request is a separate choice when the answer depends on new information from an external operation.

OpenAI documents fine-tuning for GPT-4o, and its optimisation guide specifically names the August 6, 2024 snapshot for vision fine-tuning with image examples. That snapshot-specific customisation workflow is distinct from an ordinary request to the model alias. For daily writing, analysis or extraction, begin with a useful brief and an example of the desired output. A follow-up can resolve one missing fact, revise a field or refine the same artifact while preserving the task’s evidence and constraints.

**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-4o:batch`

[`openai/gpt-4o:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-4o%3Abatch&route=Ultra&caller=openai%2Fgpt-4o%3Abatch&fmt=batches)

OpenAI /`openai/gpt-4o:batch`

### Overview

GPT-4o combines text and image understanding with writing, coding, Structured Outputs and application tools. Use it to develop an evidence-based response, interpret visual material or return defined fields from a substantial source collection.

Accepted inputs

Text

Results

Text

### Available in Ailoot · inputs & methods

**Ailoot Ultra · Batch** `POST /v1/batches`

Input types

`text`

Output types

`text`

Output format

inline results\[\].response.body JSON

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`endpoint` | Type`string` | RequirementRequired | Values & limits /v1/chat/completions | Default— |
| Field`model` | Type`string` | RequirementRequired | Values & limits openai/gpt-4o:batch | Default— |
| Field`requests` | Type`batch_item[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— |
| Field`requests[].custom_id` | Type`string` | RequirementRequired | Values & limits | Default— |
| Field`requests[].body.messages` | Type`message[]` | RequirementRequired | Values & limits | Default— |
| Field`completion_window` | Type`string` | RequirementOptional | Values & limits 24h | Default— |
| Field`provider` | Type`object\|null` | RequirementOptional | Values & limits | Default— |
| Field`requests[].body.model` | Type`string` | RequirementOptional | Values & limits openai/gpt-4o:batch, openai/gpt-4o | Default— |
| Field`provider.only` | Type`string[]` | RequirementOptional | Values & limits openai | Default— |
| Field`provider.allow_fallbacks` | Type`boolean\|null` | RequirementOptional | Values & limits false, null | Default— |

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractendpoint, model, requests |
| Parameter`material_types` | Contracttext |
| Parameter`representation` | Contractinline requests\[\]; each item has custom\_id and body |
| Parameter`request_endpoint_profile` | Contract/v1/chat/completions |
| Parameter`file_material` | ContractCaller may read actual UTF-8 JSONL locally into requests\[\]. No upload purpose, input\_file\_id or file reference is used. Missing/empty customer material stops preparation before POST. |
| Parameter`serialization_order` | Contractendpoint, model, provider (if supplied), completion\_window (if supplied), requests last |
| Parameter`optional_controls` | Contractprovider.only, provider.allow\_fallbacks, completion\_window |
| Parameter`schema_scope` | ContractText Chat Completions bodies in the documented inline Batch envelope. |

Lifecycle: `asynchronous`

`GET /v1/batches/{operation_id}` · actual original create response.id; same user/key/group

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Not specified When fast mode is selected

Flex mode

Not specified When flex mode is selected

Maximum reasoning effort

Not specified When maximum reasoning effort uses the default adjustment

Explicit cache pricing

Not enabled When explicit cache is requested

#### Ailoot rates

#### Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

| Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge |
| --- | --- | --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.01** / 1K tokens Input · Cache read **$0.00125** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.01** / 1K tokens Input · Cache read **$0.00125** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · Batch

curl · retained fixturePython HTTP · actual customer JSONLPython · save every completed result

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
python3 - <<'PY_REQUEST'
import json
from pathlib import Path
body=json.loads('{"endpoint":"/v1/chat/completions","model":"openai/gpt-4o:batch","requests":[{"custom_id":"req-0001","body":{"messages":[{"role":"user","content":"Hello!"}],"max_tokens":16}}]}')
Path("batch-request.json").write_text(json.dumps(body,ensure_ascii=False),encoding="utf-8")
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/batches \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @batch-request.json -D batch-response-headers.txt -o batch-create-response.json
```

```python
import json, os
from pathlib import Path
from urllib.request import Request, urlopen

def prepare_requests(customer_path):
    path = Path(customer_path)
    if not path.is_file(): raise ValueError("Customer JSONL file is missing")
    items = [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()]
    if not items: raise ValueError("Customer JSONL contains no requests")
    ids = set()
    for item in items:
        if set(item) != {"custom_id", "body"}: raise ValueError("Each item needs custom_id and body")
        cid = item["custom_id"]
        if not isinstance(cid, str) or not cid.strip() or cid in ids: raise ValueError("custom_id must be nonempty and unique")
        ids.add(cid)
        if not isinstance(item["body"], dict) or not item["body"].get("messages"): raise ValueError("Supply actual text messages")
        supplied_model = item["body"].get("model")
        if supplied_model is not None and supplied_model not in ['openai/gpt-4o:batch', 'openai/gpt-4o']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"openai/gpt-4o:batch", "requests":items}

if __name__ == "__main__":
    material = os.environ.get("AILOOT_BATCH_REQUESTS_JSONL", "")
    if not material: raise SystemExit("Set AILOOT_BATCH_REQUESTS_JSONL to your actual customer file")
    body = prepare_requests(material)
    key = os.environ.get("AILOOT_API_KEY", "")
    if not key: raise SystemExit("Set AILOOT_API_KEY")
    request = Request("https://api.ailoot.ai/v1/batches", data=json.dumps(body, ensure_ascii=False).encode("utf-8"), headers={"Authorization":"Bearer " + key, "Content-Type":"application/json"}, method="POST")
    with urlopen(request) as response:
        raw = response.read()
        Path("batch-create-response.json").write_bytes(raw)
        print(raw.decode("utf-8"))
```

```python
import json
from pathlib import Path
raw = Path("batch-status-response.json").read_bytes()
response = json.loads(raw)
if response.get("status") != "completed":
    raise SystemExit("Keep the original operation; read its status without resubmitting")
results = response.get("results")
if not isinstance(results, list) or not results:
    raise SystemExit("Preserve the original response; completed results are missing")
Path("batch-results.jsonl").write_text("".join(json.dumps(item, ensure_ascii=False) + "\n" for item in results), encoding="utf-8")
# Preserve batch-status-response.json with aggregate usage and every result/error.
```

### Receive and save results

#### Ailoot Ultra · Batch

inline results\[\].response.body JSON

- `GET /v1/batches/{operation_id}`

##### Check job status

curl · original operation status

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
BATCH_OPERATION_ID="$(python3 - <<'PY_ID'
import json
from pathlib import Path
from urllib.parse import quote
response = json.loads(Path("batch-create-response.json").read_text(encoding="utf-8"))
operation = response.get("id")
if not isinstance(operation, str) or not operation: raise SystemExit("No actual original operation ID; preserve the response and do not resubmit")
print(quote(operation, safe=""))
PY_ID
)"
curl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/batches/$BATCH_OPERATION_ID" \
  -H "Authorization: Bearer $AILOOT_API_KEY" -o batch-status-response.json
```

##### Keep all completed results

Keep every complete returned response, file and content part.

Preserve the full original status JSON, every result/custom\_id and complete response or error body. Save completed results\[\] as JSONL without filtering.

##### If the original response needs checking

Preserve the original operation ID. 503 result\_pending\_check has X-Should-Retry:false; never resubmit an unknown original batch.

Response fields

| Field | Type |
| --- | --- |
| Field`results[].custom_id` | Typestring |
| Field`results[].response.body.choices[].message.content` | Typestring\|null |
| Field`results[].error` | Typeobject\|null |
| Field`usage` | Typeobject\|null |
| Field`id` | Typestring |
| Field`model` | Typestring |
| Field`endpoint` | Typestring |
| Field`status` | Typestring |
| Field`request_counts` | Typeobject |
| Field`results[].id` | Typestring |
| Field`results[].response.status_code` | Typeinteger |
| Field`results[].response.request_id` | Typestring |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid documented inline envelope, duplicate keys, item identity, or configured model capabilities conflict. | Next stepCorrect the indicated fields before any new submission. |
| Response401 · `authentication_error` | ConditionInvalid API key. | Next stepUse the authorized Ailoot key. |
| Response403 · `permission_error` | ConditionBatch group unavailable. | Next stepCheck key/group entitlement. |
| Response422 · `invalid_request_error` | ConditionBatch uses balance billing; subscription creation is rejected. | Next stepUse the authorized balance-billed group. |
| Response422 · `price_unavailable` | ConditionBatch input cannot be quoted. | Next stepPreserve response; use documented family input. |
| Response402 · `billing_error` | ConditionBatch reserve unavailable. | Next stepResolve admission before a new request. |
| Response503 · `price_unavailable` | ConditionBatch method price/native rates unavailable. | Next stepPreserve response; do not substitute prices. |
| Response503 · `api_error` | ConditionExact supplier route unavailable. | Next stepPreserve response for route repair. |
| Response503 · `result_pending_check` | ConditionOriginal result requires checking; X-Should-Retry:false. | Next stepKeep original operation\_id/id and read its status; never repeat original POST. |
| Response404 · `not_found` | ConditionBatch status operation absent or owned by another identity. | Next stepUse exact original id and same user/key/group. |

### Aliases

#### Model aliases

**Ailoot Ultra** [`openai/gpt-4o:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-4o%3Abatch&route=Ultra&caller=openai%2Fgpt-4o%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

[`openai/gpt-4o:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-4o%3Abatch&route=Ultra&caller=openai%2Fgpt-4o%3Abatch&fmt=batches)

FAQ · OpenAI: GPT-4o (batch)

What inputs and results are available?

`POST /v1/batches` · `openai/gpt-4o:batch`: `text` → `text`

Which fields does the request use?

`POST /v1/batches` · `openai/gpt-4o:batch`: `endpoint`, `model`, `requests`, `completion_window`, `provider`

What limits apply?

`POST /v1/batches` · `openai/gpt-4o:batch`: `requests.min_items`: `1`

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