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

# OpenAI: GPT-6 Sol (batch)

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

GPT-6 Sol is OpenAI’s reasoning model for complex coding and agentic workflows. It connects text and image context with a defined implementation or analytical result, using configurable reasoning, structured outputs and a 1,050,000-token producer context.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `openai/gpt-6-sol:batch`](https://ailoot.ai/models/en/openai-gpt-6-sol-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 Sol is OpenAI’s reasoning model for complex coding and agentic workflows. It works with text and images and returns text such as an explanation, implementation, structured record or proposed tool operation. The named GPT-6 Sol edition remains separate from the newer GPT-6.1 Sol and from Sol’s Pro execution mode, so its controls and knowledge profile should be retained when comparing results across editions.

#### Coding from a concrete brief

Provide the relevant implementation, observed behaviour, expected behaviour and conditions the change must preserve. Identify the final artifact and the observations needed to establish completion. An illustrative assignment is: “Locate why this input fails, propose the smallest correction and return the changed function with a source-based explanation of the condition it handles.”

For a multi-file task, name the affected modules and the interfaces between them. For a visual interface, combine the code and behavioural requirements with a readable screenshot or mockup and identify the visible states to implement. Generated code is a proposed artifact until it runs in the intended application; actual errors or rendered states are the evidence for the next revision.

#### Reasoning and task depth

The producer supports none, low, medium, high, xhigh and max reasoning effort, defaulting to medium. Effort selects the amount of reasoning; standard and Pro mode describe a separate execution choice. A direct task can use none, while more complex debugging or planning can benefit from deliberate analysis. Define the required final answer separately from its intermediate process.

A source-based analytical task should name the decision, comparison criteria and authoritative material. Ask the result to connect each conclusion with the supplied passage and to state missing information. This keeps the goal visible even when the model chooses several tool steps.

#### Context and limits

The published profile has a 1,050,000-token context, a maximum input of 922,000 tokens and a maximum output of 128,000 tokens, with an April 20, 2026 knowledge cutoff. Reasoning consumes part of the response budget and context. Leave room for analysis, tool observations and the final result, and inspect an incomplete response before treating the task as finished.

#### Producer tools and interfaces

Use the documented Responses workflow for built-in tools and function calling. OpenAI’s Chat Completions profile supports function calling with reasoning effort set to none. The card lists streaming and Structured Outputs and tools for web search, file search, image generation, code interpretation, shell operations, patching, skills, computer use, MCP connections and tool discovery. The model returns text; an executed operation or generated image belongs to the corresponding tool result.

The surrounding application defines and performs operations and returns observations. Keep the actual result with its call identifier and source. The GPT-6 family guide also describes asynchronous tool work, steering an active turn, persisted reasoning and conversation compaction for longer tasks.

#### Reviewable output

A useful handoff contains the implementation or conclusion, the evidence supporting it and any condition still unresolved. Check source-derived values and generated code against the requirements. The task should end when the stated artifact and completion criterion have been met, rather than treating a plan or proposed validation command as proof of executed work.

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

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

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

### Overview

GPT-6 Sol is OpenAI’s reasoning model for complex coding and agentic workflows. It connects text and image context with a defined implementation or analytical result, using configurable reasoning, structured outputs 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-6-sol: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-sol:batch, openai/gpt-6-sol | 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 **$0.01** / 1K tokens Input · Cache read **$0.0002** / 1K tokens Input · Cache write **$0.0025** / 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 **$0.01** / 1K tokens Input · Cache read **$0.0002** / 1K tokens Input · Cache write **$0.0025** / 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 **$0.015** / 1K tokens Input · Cache read **$0.0004** / 1K tokens Input · Cache write **$0.005** / 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-sol: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-sol:batch', 'openai/gpt-6-sol']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"openai/gpt-6-sol: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-sol:batch`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-sol%3Abatch&route=Ultra&caller=openai%2Fgpt-6-sol%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

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

FAQ · OpenAI: GPT-6 Sol (batch)

What inputs and results are available?

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

Which fields does the request use?

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

What limits apply?

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

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