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

# OpenAI: GPT-6 Astra (batch)

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

GPT-6 Astra is OpenAI’s model for demanding reasoning, software engineering, research and professional document work. It combines text and image understanding with long-context analysis and tool-guided workflows, producing a text result within a 1,050,000-token context.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-6-astra:batch`](https://ailoot.ai/models/en/openai-gpt-6-astra-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 is OpenAI’s model for its most demanding reasoning and professional tasks. The producer develops it for software engineering, computer use, research, scientific work and document creation. It accepts text and images and generates text, including explanations, code and structured artifacts. This standard Astra profile is separate from Pro reasoning mode and the Sol and Luna profiles.

#### End-to-end work

Prepare the assignment around the desired outcome, relevant sources and criteria for completion. For software engineering, include the code, observed failure, expected behaviour and interfaces to preserve. For professional analysis, provide the documents, the decision and the conditions that a conclusion must address. A practical brief is: “Compare these alternatives against the requirements, identify the dependencies and produce a decision memo with evidence for every material finding.”

For a visual task, make the source readable and identify whether it shows an interface state, chart or design requirement. Ask for the visible detail supporting an observation. A code or document artifact should remain tied to that evidence rather than an assumed external action.

#### Prompting and follow-through

OpenAI’s Astra guidance recommends clear goals, success criteria, evidence rules and stopping conditions. It notes strong sensitivity to detailed instructions in context and accessible files, so resolve conflicting guidance and state the priority of the user’s task. Specify when the model should use available information, make a reasonable assumption or ask for a missing detail that changes the outcome.

The maker also recommends calibrating response style and validation depth. Describe the audience and final structure for a document, and require validation relevant to the change for an engineering task. This gives the model an explicit finish line without adding unrelated work.

#### Reasoning and context

Astra supports low, medium, high, xhigh and max reasoning effort and does not support none. Effort is distinct from the producer’s standard or Pro reasoning mode. The card lists a 1,050,000-token context, up to 922,000 input tokens and up to 128,000 output tokens. Its knowledge cutoff is April 30, 2026.

Reasoning occupies response space even though the raw internal tokens are not exposed as an ordinary answer. Reserve room for the final artifact and inspect termination status when a budget is exhausted. A large window still needs source labels, task boundaries and relevant observations.

#### Tools and continuing tasks

The producer documents function calling through Responses; Chat Completions does not support function calling for Astra. Its supported tools include web and file search, image generation, a code interpreter, shell and patch operations, skills, computer use, MCP connections and tool search. Structured Outputs and streaming are also listed. Astra’s own output remains text, while tool operations produce their respective observations or artifacts.

GPT-6’s documented workflow can continue analysis while an asynchronous tool runs, incorporate mid-turn steering, preserve reasoning between calls and compact a long conversation. The application executes its own tools and manages pending results. Retain the original call and observation association so the task uses actual evidence.

A useful final result is a completed analytical or code artifact with its basis and remaining conditions explicit. Review source-dependent statements and use actual validation observations for executed work. Keep the named Astra profile and its supported effort range instead of borrowing a direct-response setting or another model’s limits.

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

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

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

### Overview

GPT-6 Astra is OpenAI’s model for demanding reasoning, software engineering, research and professional document work. It combines text and image understanding with long-context analysis and tool-guided workflows, producing a text result within a 1,050,000-token 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-6-astra: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:batch, openai/gpt-6-astra | 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: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:batch', 'openai/gpt-6-astra']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"openai/gpt-6-astra: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:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-astra%3Abatch&route=Ultra&caller=openai%2Fgpt-6-astra%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

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

FAQ · OpenAI: GPT-6 Astra (batch)

What inputs and results are available?

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

Which fields does the request use?

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

What limits apply?

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

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