Source: https://ailoot.ai/models/en/anthropic-claude-sonnet-4-5-u003a-batch/
Canonical: https://ailoot.ai/models/en/anthropic-claude-sonnet-4-5-u003a-batch/
Language: en

# Anthropic: Claude Sonnet 4.5 (batch)

[Markdown](https://ailoot.ai/models/en/anthropic-claude-sonnet-4-5-u003a-batch/index.md) · [JSON](https://ailoot.ai/models/en/anthropic-claude-sonnet-4-5-u003a-batch/facts.json)

## [Anthropic: Claude Sonnet 4.5 (batch)](https://ailoot.ai/models/en/anthropic-claude-sonnet-4-5-u003a-batch/)

Claude Sonnet 4.5 is Anthropic’s text-and-image model for software development, complex agents, computer use and analytical work. It supports direct responses or manual extended thinking, with reasoning between tool calls in the documented beta workflow.

- [**Ailoot Ultra · Batch** `POST /v1/batches` `anthropic/claude-sonnet-4.5:batch`](https://ailoot.ai/models/en/anthropic-claude-sonnet-4-5-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.

Claude Sonnet 4.5 is Anthropic’s Sonnet edition focused on software development, complex agent tasks and computer use, with improvements in reasoning and mathematics. It accepts text and images and generates text. The release describes sustained work across multiple steps, code comprehension and changes that involve a broader project rather than a single isolated function. A useful brief identifies the required behaviour, the relevant source material and the artifact to deliver: a proposed patch, an implementation explanation, a document analysis or a structured answer.

For software work, provide the project’s constraints, the relevant files or excerpts, the observed error and a concrete example of the expected result. Ask for the affected code and an explanation of how the proposed change addresses that example. The producer presents the model as suitable for building agents and working through development tasks with tools. The surrounding application reads and edits files, runs a command or check and returns its actual output; the model reasons over that evidence. Keep the proposed change and the completed check distinct in the final report.

Computer use is a separate application of its visual and agent capabilities. Anthropic’s release demonstrates browser interaction, navigating pages and working with spreadsheets through a connected environment. A visual brief can supply a screenshot, identify the goal and define which actions the application permits. The application then performs the selected interaction and returns the changed screen or other result. Similarly, the model can prepare content and code for documents, spreadsheets and slides, while the environment produces the finished file. Text-and-image understanding does not make the model a native image or audio generator.

The exact producer specification lists a 200K-token context window and up to 64K output tokens. Its reliable knowledge cutoff is January 2025, distinct from the later training-data cutoff listed on the page. Keep document boundaries, page labels, units and code identifiers clear in a long input, and reserve space for the requested answer and any reasoning. The producer also documents context awareness for this edition, so its supported workflow tracks the space remaining during a conversation. That helps manage a sustained task within its window; it does not replace the window with a later Sonnet edition’s larger capacity.

Sonnet 4.5 supports ordinary responses and manual extended thinking. In the latter mode, budget\_tokens sets a target for the internal reasoning before the visible answer. The documented minimum is 1,024 tokens, and the budget normally must be lower than max\_tokens because thinking and the final answer share the generation allowance. The budget is a target rather than a promise to consume exactly that many tokens. This edition does not have the adaptive-thinking mode or effort controls described for later Sonnet models. Choose the requested analysis depth and leave enough allowance for a usable final answer.

The producer’s interleaved-thinking beta lets Sonnet 4.5 reason between tool calls within a turn, using the returned observations to decide its next step. It requires the documented beta feature in the supported Messages workflow. In this case, the thinking budget can exceed max\_tokens because it spans multiple thinking blocks in the same assistant turn. Return tool results with the associated thinking content unmodified, including its signature; editing that content invalidates it. A research or debugging task can therefore alternate a proposed check, the real returned result and an updated analysis without treating a textual proposal as a completed action.

For visual material, the producer supports JPEG, PNG, GIF and WebP and uses only the first frame of an animation. The standard native image tier used by this edition has a 1,568-pixel long-edge limit and a 1,568-visual-token limit; larger images are downscaled. The producer’s image guide lists up to 100 images per API request for 200K-context models, with image and overall request-size conditions that can be reached first. Put images before the question when practical, label multiple images and preserve small text or chart labels. The guide recommends clear images and retaining enough surrounding context to interpret the visible detail.

Context editing and a memory tool were introduced alongside this model to support longer agent workflows. These are application-supported ways to retain useful state or remove old tool material; they are not an unlimited model memory or the later server-compaction feature. For a multi-stage task, preserve the decisions already made, the outstanding question and the evidence needed for the next step. Anthropic also describes stronger resistance to hidden instructions in external content, while noting that model-specific classifiers can sometimes flag benign material. The useful result remains a reviewable artifact tied to supplied evidence, with the exact Sonnet 4.5 modes and limits kept separate from later releases.

**Ailoot Ultra · Batch** `POST /v1/batches` `anthropic/claude-sonnet-4.5:batch`

[`anthropic/claude-sonnet-4.5:batch`](https://ailoot.ai/models/en/#m=anthropic%2Fclaude-sonnet-4.5%3Abatch&route=Ultra&caller=anthropic%2Fclaude-sonnet-4.5%3Abatch&fmt=batches)

Anthropic /`anthropic/claude-sonnet-4.5:batch`

### Overview

Claude Sonnet 4.5 is Anthropic’s text-and-image model for software development, complex agents, computer use and analytical work. It supports direct responses or manual extended thinking, with reasoning between tool calls in the documented beta workflow.

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-sonnet-4.5: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-sonnet-4.5:batch, anthropic/claude-sonnet-4.5 | 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 **$0.003** / 1K tokens Output · Output tokens **$0.015** / 1K tokens Input · Cache read **$0.0003** / 1K tokens Input · Cache write **$0.00375** / 1K tokens Input · Cache write, 1 hour **$0.006** / 1K tokens |
| ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens **$0.003** / 1K tokens Output · Output tokens **$0.015** / 1K tokens Input · Cache read **$0.0003** / 1K tokens Input · Cache write **$0.00375** / 1K tokens Input · Cache write, 1 hour **$0.006** / 1K tokens |
| ConfigurationRequest-length tier 2 | Rate schedule— | Context tokens, more than200,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.006** / 1K tokens Output · Output tokens **$0.0225** / 1K tokens Input · Cache read **$0.0006** / 1K tokens Input · Cache write **$0.0075** / 1K tokens Input · Cache write, 1 hour **$0.012** / 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-sonnet-4.5: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-sonnet-4.5:batch', 'anthropic/claude-sonnet-4.5']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"anthropic/claude-sonnet-4.5: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-sonnet-4.5:batch`](https://ailoot.ai/models/en/#m=anthropic%2Fclaude-sonnet-4.5%3Abatch&route=Ultra&caller=anthropic%2Fclaude-sonnet-4.5%3Abatch&fmt=batches)

#### Method path aliases

Use the method paths shown above.

#### Related caller IDs

[`anthropic/claude-sonnet-4.5:batch`](https://ailoot.ai/models/en/#m=anthropic%2Fclaude-sonnet-4.5%3Abatch&route=Ultra&caller=anthropic%2Fclaude-sonnet-4.5%3Abatch&fmt=batches)

FAQ · Anthropic: Claude Sonnet 4.5 (batch)

What inputs and results are available?

`POST /v1/batches` · `anthropic/claude-sonnet-4.5:batch`: `text` → `text`

Which fields does the request use?

`POST /v1/batches` · `anthropic/claude-sonnet-4.5:batch`: `endpoint`, `model`, `requests`, `completion_window`, `provider`

What limits apply?

`POST /v1/batches` · `anthropic/claude-sonnet-4.5:batch`: `requests.min_items`: `1`

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