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

# OpenAI: GPT-5.5 (batch)

[Markdown](https://ailoot.ai/models/en/openai-gpt-5-5-u003a-batch/index.md) · [JSON](https://ailoot.ai/models/en/openai-gpt-5-5-u003a-batch/facts.json)

## [OpenAI: GPT-5.5 (batch)](https://ailoot.ai/models/en/openai-gpt-5-5-u003a-batch/)

OpenAI’s GPT-5.5 handles complex professional work and coding with text and image inputs, configurable reasoning, and a broad tool set. Its large context supports working across substantial source material and returning a clear, task-specific text result.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-5.5:batch`](https://ailoot.ai/models/en/openai-gpt-5-5-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-5.5 is OpenAI’s flagship reasoning model for complex professional work and coding. It accepts text and images and returns text, combining analysis with tool use when a task needs information or actions beyond the supplied prompt. OpenAI’s guidance emphasizes working from a clear outcome: explain the result you need, the constraints that must hold, the evidence to use and the condition that ends the task.

For a substantial software change, provide the relevant repository material, the current behavior, the desired behavior and the acceptance criteria. Identify what can be changed and what must remain compatible. A useful requested result is a proposed change, an explanation of the affected behavior and evidence from any checks that actually ran. For a document-heavy task, label the source documents and ask for an answer organized around the decision you need to make, with each conclusion tied to the supplied evidence and unresolved questions separated from established facts.

GPT-5.5 supports none, low, medium, high and xhigh reasoning effort, with medium as the default. OpenAI recommends considering low before none when a responsive workflow still needs planning, search or several tool calls. None is suited to direct tasks that do not need that reasoning process. Higher effort is not automatically better: conflicting requirements, open-ended tool access or an unclear stopping rule can lead to unnecessary searching and overthinking. Choose the effort for the actual task, and make the expected final artifact and completion criterion explicit.

The producer lists a 1,050,000-token context window and a maximum output of 128,000 tokens, with a knowledge cutoff of December 1, 2025. The context accommodates the conversation, supplied material and generated content; it is not a separate allowance to add to the maximum output. Internal reasoning also consumes tokens and output capacity. A large source collection should therefore be organized around the question, with important identifiers, units and document boundaries retained and enough room left for the reasoning and final answer.

Image handling differs from earlier defaults. In OpenAI’s GPT-5.5 guidance, an unset or auto image-detail setting uses original behavior, preserving an image without resizing when it stays within both the stated 10,240,000-pixel budget and the 6,000-pixel maximum dimension. An explicitly selected high setting preserves detail within both the stated 2,500,000-pixel budget and the 2,048-pixel maximum dimension; low resizes images above a 512-pixel dimension more aggressively. These are image-processing settings, not a guarantee that every upload is accepted. For a screenshot, diagram or page, identify the region and question, supply a legible image, and request the observation or interpretation you need rather than an unrestricted description.

OpenAI documents Responses, Chat Completions and Batch interfaces, with streaming, Structured Outputs, function calling, file uploads, image input, file and web search, and prompt caching. The documented tool set also includes tool search, image generation, code interpretation, hosted shell, patch operations, skills, computer use and MCP. Describe each application tool’s purpose, arguments, side effects and returned information. A request to call an application function needs the application to execute that operation and return its actual result; a generated action proposal is not evidence that the action occurred. The model’s own output modality remains text, while an image-generation tool can produce a separate artifact.

For longer interactions, preserve the information needed to distinguish interim work from a finished answer. OpenAI’s guide describes assistant phase values for commentary and final answers: applications that manually replay assistant items must retain their original phase values, while chaining through the producer’s previous-response mechanism preserves that state automatically. For the visible answer, set the desired length, tone and structure explicitly. GPT-5.5 defaults to a concise, direct style, and text verbosity defaults to medium; a compact result can request lower verbosity without removing required evidence or qualifications.

A useful final deliverable can be a revised file with a focused change explanation, a decision memo grounded in named documents, or a structured extraction with missing values clearly marked. Supply facts that must be current instead of relying on the model’s knowledge cutoff, and compare important claims with the original material. Clear evidence rules, bounded tools and explicit stopping conditions help GPT-5.5 complete a substantial task while keeping the result understandable and reviewable.

**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-5.5:batch`

[`openai/gpt-5.5:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-5.5%3Abatch&route=Ultra&caller=openai%2Fgpt-5.5%3Abatch&fmt=batches)

OpenAI /`openai/gpt-5.5:batch`

### Overview

OpenAI’s GPT-5.5 handles complex professional work and coding with text and image inputs, configurable reasoning, and a broad tool set. Its large context supports working across substantial source material and returning a clear, task-specific text result.

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-5.5: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-5.5:batch, openai/gpt-5.5 | 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 **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 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 **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 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 **$0.01** / 1K tokens Output · Output tokens **$0.045** / 1K tokens Input · Cache read **$0.001** / 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-5.5: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-5.5:batch', 'openai/gpt-5.5']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"openai/gpt-5.5: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-5.5:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-5.5%3Abatch&route=Ultra&caller=openai%2Fgpt-5.5%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

[`openai/gpt-5.5:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-5.5%3Abatch&route=Ultra&caller=openai%2Fgpt-5.5%3Abatch&fmt=batches)

FAQ · OpenAI: GPT-5.5 (batch)

What inputs and results are available?

`POST /v1/batches` · `openai/gpt-5.5:batch`: `text` → `text`

Which fields does the request use?

`POST /v1/batches` · `openai/gpt-5.5:batch`: `endpoint`, `model`, `requests`, `completion_window`, `provider`

What limits apply?

`POST /v1/batches` · `openai/gpt-5.5:batch`: `requests.min_items`: `1`

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