Source: https://ailoot.ai/models/en/anthropic-claude-opus-4-6-u003a-batch/
Canonical: https://ailoot.ai/models/en/anthropic-claude-opus-4-6-u003a-batch/
Language: en

# Anthropic: Claude Opus 4.6 (batch)

[Markdown](https://ailoot.ai/models/en/anthropic-claude-opus-4-6-u003a-batch/index.md) · [JSON](https://ailoot.ai/models/en/anthropic-claude-opus-4-6-u003a-batch/facts.json)

## [Anthropic: Claude Opus 4.6 (batch)](https://ailoot.ai/models/en/anthropic-claude-opus-4-6-u003a-batch/)

Claude Opus 4.6 is designed for large codebases, debugging, research and analysis of long documents. Supports adaptive reasoning and a context window of up to 1 million tokens.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `anthropic/claude-opus-4.6:batch`](https://ailoot.ai/models/en/anthropic-claude-opus-4-6-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.

#### A large task and the connections between its parts

Claude Opus 4.6 is intended for work where it is useful to keep extensive material in one context and reason after reading it. Anthropic highlights development in large codebases, code review, debugging, financial analysis and research. The model can find important details, connect information from different parts of the material and use it to solve a task sequentially.

In development, this means working on a plan, studying an unfamiliar system and finding errors in changes. In professional analysis, it means processing documents and preparing the content of spreadsheets, reports or presentations. For these scenarios, the model needs the task itself and the material from which conclusions should be drawn, rather than just a general topic name.

#### Adaptive reasoning

The model supports adaptive mode: it determines from the prompt's content when additional analysis is useful. The `effort` parameter sets the level of work; Opus 4.6 supports `low`, `medium`, `high` and `max`, with `high` as the default. According to Anthropic, deeper analysis can increase response time on simple tasks, so the selected level should reflect their complexity.

Older extended thinking with a manual budget is still supported, but is marked as deprecated. This version has an important distinction between modes: reasoning between tool calls is available in adaptive mode, but Opus 4.6 does not perform it in manual mode. With tools connected, adaptive analysis helps use the result of one action to choose the next.

#### Context for sustained work

Anthropic's current specification provides **1 million tokens of context** and up to **128 thousand response tokens in ordinary mode**. It accepts **text and images**, with text as its response. The reliable built-in knowledge cutoff is **May 2025**.

The manufacturer's standard visual input formats are JPEG/PNG/GIF/WebP, using the first frame of an animation. For native analysis, the longer dimension is 1568 pixels, with 1568 visual tokens; larger images are downscaled before analysis. File and parameter support depends on the application's method.

For extended conversations and agentic tasks, the manufacturer describes compaction of old context: earlier work is replaced by a summary as a specified threshold approaches. This capability is marked as experimental and requires application support; context size alone does not provide unlimited memory.

#### Tools and checking the result

Opus 4.6 is designed for multi-step work with search, code and other available tools. The application environment must provide material reading, command execution or file production. Production actions, interface control and creation of a finished presentation depend on these tools; a text model does not receive them automatically.

Anthropic separately describes safety checks and protective measures for potentially dangerous cybersecurity tasks. For ordinary development, the model can help find and fix vulnerabilities, but the nature of a request affects whether it can answer. Conclusions drawn from a large body of material and proposed changes need to be checked against the actual data and execution results.

**Ailoot Ultra · Batch** `POST /v1/batches` `anthropic/claude-opus-4.6:batch`

[`anthropic/claude-opus-4.6:batch`](https://ailoot.ai/models/en/#m=anthropic%2Fclaude-opus-4.6%3Abatch&route=Ultra&caller=anthropic%2Fclaude-opus-4.6%3Abatch&fmt=batches)

Anthropic /`anthropic/claude-opus-4.6:batch`

### Overview

Claude Opus 4.6 is designed for large codebases, debugging, research and analysis of long documents. Supports adaptive reasoning and a context window of up to 1 million tokens.

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 anthropic/claude-opus-4.6: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 anthropic/claude-opus-4.6:batch, anthropic/claude-opus-4.6 | Default— |
| Field`provider.only` | Type`string[]` | RequirementOptional | Values & limits anthropic | 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

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 **$0.025** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00625** / 1K tokens Input · Cache write, 1 hour **$0.01** / 1K tokens |
| ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.025** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00625** / 1K tokens Input · Cache write, 1 hour **$0.01** / 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":"anthropic/claude-opus-4.6: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 ['anthropic/claude-opus-4.6:batch', 'anthropic/claude-opus-4.6']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"anthropic/claude-opus-4.6: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** [`anthropic/claude-opus-4.6:batch`](https://ailoot.ai/models/en/#m=anthropic%2Fclaude-opus-4.6%3Abatch&route=Ultra&caller=anthropic%2Fclaude-opus-4.6%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

[`anthropic/claude-opus-4.6:batch`](https://ailoot.ai/models/en/#m=anthropic%2Fclaude-opus-4.6%3Abatch&route=Ultra&caller=anthropic%2Fclaude-opus-4.6%3Abatch&fmt=batches)

FAQ · Anthropic: Claude Opus 4.6 (batch)

What inputs and results are available?

`POST /v1/batches` · `anthropic/claude-opus-4.6:batch`: `text` → `text`

Which fields does the request use?

`POST /v1/batches` · `anthropic/claude-opus-4.6:batch`: `endpoint`, `model`, `requests`, `completion_window`, `provider`

What limits apply?

`POST /v1/batches` · `anthropic/claude-opus-4.6:batch`: `requests.min_items`: `1`

Connect Ailoot to Claude Code, OpenCode, Hermes or your own app.

## The company and its project portfolio

The company and its project portfolio: millions of customers; monthly sales in the billions.

## Buy tokens at a discount.

Subscription discounts for regular use. Promo codes offer up to 50% off token purchases.

Subscription

Choose a discounted plan for your regular requests.

Promo code: up to 50% off

Enter your code at checkout. The price updates to reflect the current promotion.

Spending in your history

The model, tokens and amount are recorded for each request.

[Choose a subscription](https://ailoot.ai/docs/en/billing/subscriptions/) · [View model prices](https://ailoot.ai/models/en/)

## Connect the API to a product you sell.

Use Ailoot in SaaS, apps and bots under its official service offer and licence agreement. Request a reseller licence for resale.

Commercial application

Add text, image, video and audio generation to paid features in your service.

Reseller licence

Send a description of your project and how you provide access. Request written terms for use and resale.

Documents on the website

The service offer, licence agreement and data processing policy are available before you connect.

[Request a reseller licence](mailto:support@ailoot.ai) · [Service offer and licence agreement](https://ailoot.ai/legal/offer?lang=en)

## Ailoot · The company and its project portfolio





Ailoot combines established operating experience, a large client base, stable service and ongoing KPI control.





The company and its project portfolio: millions of customers; monthly sales in the billions.





Ailoot brings that operating experience to API access for AI features in customer products, agents, applications and automations.
