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

# OpenAI: GPT-5.6 Terra (batch)

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## [OpenAI: GPT-5.6 Terra (batch)](https://ailoot.ai/models/en/openai-gpt-5-6-terra-u003a-batch/)

GPT-5.6 Terra is OpenAI’s balanced reasoning model for analysis, drafting and multi-step assistance. It uses text and images to produce explanations, code or structured findings, with configurable effort and a 1,050,000-token producer context.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-5.6-terra:batch`](https://ailoot.ai/models/en/openai-gpt-5-6-terra-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 Terra is OpenAI’s balanced model in the GPT-5.6 family. The producer relates its workload role to the mini tier used in earlier GPT-5 families, while Terra retains its own named profile. It works with text and images and returns text such as an explanation, draft, code proposal or structured analytical record.

#### Analysis with a defined outcome

Provide the source material, the question and the criteria for a conclusion. A practical brief is: “Compare these requirements with the proposal, identify each mismatch and return the supporting passage, consequence and unresolved question.” Label the documents and preserve terms or units that affect their meaning. The result should identify what the material establishes and what remains an assumption.

For writing, define the audience, tone and facts that must remain. For a revision, name the passage to change and the meaning to preserve. For a coding task, give the relevant implementation, observed failure and required behaviour. A focused artifact is more useful than a broad instruction to improve an unspecified collection of material.

#### Reasoning depth and mode

The model supports none, low, medium, high, xhigh and max reasoning effort, defaulting to medium. Effort controls the depth of analysis, while standard or Pro mode is a separate execution choice. A task’s final output contract remains important at every setting: identify the answer language, required fields and criteria for completion.

OpenAI describes available earlier reasoning being rendered into subsequent GPT-5.6 turns by default, with a context control for supported workflows. This can support a continuing analysis, while retained material still uses context. Keep the accepted facts and new observations distinguishable from tentative intermediate conclusions.

#### Input and output limits

Terra’s published context is 1,050,000 tokens, with up to 922,000 input tokens and up to 128,000 output tokens. Its knowledge cutoff is February 16, 2026. Source, history, tool results, reasoning and the visible answer need room together. Reserve space for a complete final artifact and inspect incomplete responses before treating a task as finished.

For visual material, preserve readable text, labels and surrounding context. Ask the answer to identify the image detail supporting a conclusion. The model processes text and images into text; rendered media or executed application actions are different results.

#### Tools and structured artifacts

The producer lists function calling, Structured Outputs and streaming, plus web and file search, image-generation tooling, a code interpreter, shell and patch operations, skills, computer use, MCP connections and tool search. The surrounding application performs its selected operations and returns observations so the model can continue.

Give functions precise purposes and parameter schemas. For a structured record, define each field and how to represent missing evidence, then compare returned values with the source. A format-conforming answer does not itself prove retrieval, execution or validation.

A useful final result is a reviewable draft, source comparison, code proposal or data record tied to the task’s requirements and observations. Use Terra’s supported reasoning settings and limits when preparing the task; Sol and GPT-6 have their own profiles.

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

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

OpenAI /`openai/gpt-5.6-terra:batch`

### Overview

GPT-5.6 Terra is OpenAI’s balanced reasoning model for analysis, drafting and multi-step assistance. It uses text and images to produce explanations, code or structured findings, with configurable effort and a 1,050,000-token producer context.

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-terra: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-terra:batch, openai/gpt-5.6-terra | 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 **$0.002** / 1K tokens Output · Output tokens **$0.012** / 1K tokens Input · Cache read **$0.0002** / 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 **$0.002** / 1K tokens Output · Output tokens **$0.012** / 1K tokens Input · Cache read **$0.0002** / 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 **$0.004** / 1K tokens Output · Output tokens **$0.018** / 1K tokens Input · Cache read **$0.0004** / 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-terra: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-terra:batch', 'openai/gpt-5.6-terra']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"openai/gpt-5.6-terra: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-terra:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-5.6-terra%3Abatch&route=Ultra&caller=openai%2Fgpt-5.6-terra%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

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

FAQ · OpenAI: GPT-5.6 Terra (batch)

What inputs and results are available?

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

Which fields does the request use?

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

What limits apply?

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

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