Source: https://ailoot.ai/models/en/openai-gpt-5-6-luna-pro-u003a-batch/
Canonical: https://ailoot.ai/models/en/openai-gpt-5-6-luna-pro-u003a-batch/
Language: en

# OpenAI: GPT-5.6 Luna Pro (batch)

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## [OpenAI: GPT-5.6 Luna Pro (batch)](https://ailoot.ai/models/en/openai-gpt-5-6-luna-pro-u003a-batch/)

GPT-5.6 Luna with Pro reasoning for focused tasks that need additional analysis. Supply text or images and explicit rules to develop an extraction result, a concise response or an explanation of an exception.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-5.6-luna-pro:batch`](https://ailoot.ai/models/en/openai-gpt-5-6-luna-pro-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-5.6 Luna Pro denotes OpenAI’s GPT-5.6 Luna with Pro reasoning. The base Luna edition is designed for focused, high-volume workloads and roughly corresponds to the nano tier in earlier GPT-5 families. It accepts text and images and produces text. Pro adds model work to develop the final answer; it is an execution mode rather than a replacement for the base edition.

A practical use is extracting a defined set of information from a document whose rules include exceptions. Provide the document and the fields you need, identify any passages that take priority and explain how to handle an absent value. An illustrative request is to extract the document’s topic, the conditions relevant to a request and the next question needed to complete it. Ask for an explanation of an exception alongside the extracted fields so that the result can be compared with the source.

For visual material, supply a clear page or screenshot and identify the specific detail or label that informs the task. For a response-writing task, provide the request, the rules governing the reply and the facts that must be retained. Define the desired tone and length, then request one concise answer rather than an unrestricted discussion. This preparation connects Luna’s focused role with a concrete text result.

OpenAI specifies a 1,050,000-token context window for GPT-5.6 Luna, a maximum input of 922,000 tokens and a maximum output of 128,000 tokens, with a knowledge cutoff of February 16, 2026. The base reasoning-effort choices are none, low, medium, high, xhigh and max; medium is the default. Mode and effort are independent: Pro determines additional model work, while effort controls the amount of reasoning within the mode. Reasoning also uses context space, so allow room for analysis and the visible response.

The maker documents Pro in the Responses API for difficult tasks that can accommodate additional latency and model activity. The base model lists streaming, Structured Outputs, function calling, web and file search, image input and prompt caching. Its tool set includes image generation, code interpretation, hosted shell and patch operations, skills, computer use, MCP connections and tool search. Tool operations require the corresponding environment; an application executes its actions and supplies the actual results for continued work.

Specify a useful final artifact: required fields, the rule that supports a decision and any question still open. For example, ask for a draft reply plus the document facts it relies on, then refine the reply after providing missing information. Keep the distinction between a proposed action and an action completed by a tool visible. This workflow gives Pro’s extra analysis a specific purpose within a bounded Luna task.

**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-5.6-luna-pro:batch`

[`openai/gpt-5.6-luna-pro:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-5.6-luna-pro%3Abatch&route=Ultra&caller=openai%2Fgpt-5.6-luna-pro%3Abatch&fmt=batches)

OpenAI /`openai/gpt-5.6-luna-pro:batch`

### Overview

GPT-5.6 Luna with Pro reasoning for focused tasks that need additional analysis. Supply text or images and explicit rules to develop an extraction result, a concise response or an explanation of an exception.

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-5.6-luna-pro: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-5.6-luna-pro:batch, openai/gpt-5.6-luna-pro | 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 **$0.0002** / 1K tokens Output · Output tokens **$0.0012** / 1K tokens Input · Cache read **$0.00002** / 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 including272,000 | Charge Input · Input tokens **$0.0002** / 1K tokens Output · Output tokens **$0.0012** / 1K tokens Input · Cache read **$0.00002** / 1K tokens Input · Cache write **—** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationRequest-length tier 2 | Rate schedule— | Context tokens, more than272,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0004** / 1K tokens Output · Output tokens **$0.0018** / 1K tokens Input · Cache read **$0.00004** / 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-5.6-luna-pro: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-5.6-luna-pro:batch', 'openai/gpt-5.6-luna-pro']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"openai/gpt-5.6-luna-pro: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-5.6-luna-pro:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-5.6-luna-pro%3Abatch&route=Ultra&caller=openai%2Fgpt-5.6-luna-pro%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

[`openai/gpt-5.6-luna-pro:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-5.6-luna-pro%3Abatch&route=Ultra&caller=openai%2Fgpt-5.6-luna-pro%3Abatch&fmt=batches)

FAQ · OpenAI: GPT-5.6 Luna Pro (batch)

What inputs and results are available?

`POST /v1/batches` · `openai/gpt-5.6-luna-pro:batch`: `text` → `text`

Which fields does the request use?

`POST /v1/batches` · `openai/gpt-5.6-luna-pro:batch`: `endpoint`, `model`, `requests`, `completion_window`, `provider`

What limits apply?

`POST /v1/batches` · `openai/gpt-5.6-luna-pro:batch`: `requests.min_items`: `1`

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