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

# OpenAI: GPT-6 Astra Pro (batch)

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## [OpenAI: GPT-6 Astra Pro (batch)](https://ailoot.ai/models/en/openai-gpt-6-astra-pro-u003a-batch/)

GPT-6 Astra with Pro reasoning for demanding research, coding and professional work. Pro adds model work before the final answer; the base model accepts text and images and supports multi-step work in a tool-connected environment.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-6-astra-pro:batch`](https://ailoot.ai/models/en/openai-gpt-6-astra-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-6 Astra Pro denotes OpenAI’s GPT-6 Astra with Pro reasoning. The base Astra model is designed for demanding reasoning, coding, research, computer use and professional work. It accepts text and images and produces text. Pro adds model work when developing the final answer, while reasoning effort controls the amount of analysis within the chosen execution mode. Pro changes the execution mode while GPT-6 Astra remains the underlying model.

The manufacturer’s Astra release describes workflows that turn relevant material into documents, spreadsheets, presentations and analysis. It emphasizes following templates and writing or visual style while selecting the context that matters to the task. For a professional document, provide the source material, the template requirements and the decision the reader needs to make. An illustrative request is to reconcile two sets of project requirements and produce a brief that separates agreed facts, conflicting evidence and the conditions for a recommendation.

For engineering or research work, specify the objective, the evidence to inspect and what would count as completion. A coding task can include the required behavior, related files and constraints; a research task can include the question and the criteria for weighing the supplied material. Astra’s documented computer-use and browsing capabilities connect the model’s decisions with an environment that supplies the corresponding tools. The environment’s actual outputs are evidence for the next step, distinct from the model’s proposed actions.

OpenAI’s GPT-6 Astra specification lists a 1,050,000-token context window, a maximum input of 922,000 tokens and a maximum output of 128,000 tokens, with a knowledge cutoff of April 30, 2026. Its reasoning-effort choices are low, medium, high, xhigh and max; none is unsupported. Reasoning tokens and the visible result both occupy context space. OpenAI documents Pro in the Responses API for difficult work that can accommodate additional latency and model activity; mode and effort remain independent settings.

The base model lists streaming, Structured Outputs, function calling, web and file search, image-generation tooling, code interpretation, hosted shell and patch operations, skills, computer use, MCP connections and tool search. Function calling uses the producer’s Responses interface. The GPT-6 guide also describes asynchronous tool work and steering an active turn. Applications execute their own operations, manage pending work and return the resulting information; the model’s own output remains text even when a separate tool creates another artifact.

The Astra release describes adapting to new requirements while keeping the broader goal in view. It also distinguishes defensive code review and patching from advanced exploit-development work, which the model may refuse, and describes automatic checks that can interrupt a task. Prepare a request around the intended result, permitted work and evidence, rather than treating extra reasoning as a substitute for missing source material. A useful final artifact states the conclusion or proposed change, its basis in the supplied information and any question that would materially alter the decision.

**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-6-astra-pro:batch`

[`openai/gpt-6-astra-pro:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-astra-pro%3Abatch&route=Ultra&caller=openai%2Fgpt-6-astra-pro%3Abatch&fmt=batches)

OpenAI /`openai/gpt-6-astra-pro:batch`

### Overview

GPT-6 Astra with Pro reasoning for demanding research, coding and professional work. Pro adds model work before the final answer; the base model accepts text and images and supports multi-step work in a tool-connected environment.

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-6-astra-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-6-astra-pro:batch, openai/gpt-6-astra-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 **$0.01** / 1K tokens Output · Output tokens **$0.05** / 1K tokens Input · Cache read **$0.001** / 1K tokens Input · Cache write **$0.0125** / 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 **$0.01** / 1K tokens Output · Output tokens **$0.05** / 1K tokens Input · Cache read **$0.001** / 1K tokens Input · Cache write **$0.0125** / 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 **$0.02** / 1K tokens Output · Output tokens **$0.075** / 1K tokens Input · Cache read **$0.002** / 1K tokens Input · Cache write **$0.025** / 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-6-astra-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-6-astra-pro:batch', 'openai/gpt-6-astra-pro']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"openai/gpt-6-astra-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-6-astra-pro:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-astra-pro%3Abatch&route=Ultra&caller=openai%2Fgpt-6-astra-pro%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

[`openai/gpt-6-astra-pro:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-astra-pro%3Abatch&route=Ultra&caller=openai%2Fgpt-6-astra-pro%3Abatch&fmt=batches)

FAQ · OpenAI: GPT-6 Astra Pro (batch)

What inputs and results are available?

`POST /v1/batches` · `openai/gpt-6-astra-pro:batch`: `text` → `text`

Which fields does the request use?

`POST /v1/batches` · `openai/gpt-6-astra-pro:batch`: `endpoint`, `model`, `requests`, `completion_window`, `provider`

What limits apply?

`POST /v1/batches` · `openai/gpt-6-astra-pro:batch`: `requests.min_items`: `1`

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