models

Anthropic: Claude Opus 4.6 (batch)

Markdown · JSON

Anthropic: Claude Opus 4.6 (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.

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

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
FieldTypeRequirementValues & limitsDefault
FieldendpointTypestringRequirementRequiredValues & limits
/v1/chat/completions
Default—
FieldmodelTypestringRequirementRequiredValues & limits
anthropic/claude-opus-4.6:batch
Default—
FieldrequestsTypebatch_item[]RequirementRequiredValues & limits
Minimum items: 1
Default—
Fieldrequests[].custom_idTypestringRequirementRequiredValues & limitsDefault—
Fieldrequests[].body.messagesTypemessage[]RequirementRequiredValues & limitsDefault—
Fieldcompletion_windowTypestringRequirementOptionalValues & limits
24h
Default—
FieldproviderTypeobject|nullRequirementOptionalValues & limitsDefault—
Fieldrequests[].body.modelTypestringRequirementOptionalValues & limits
anthropic/claude-opus-4.6:batch, anthropic/claude-opus-4.6
Default—
Fieldprovider.onlyTypestring[]RequirementOptionalValues & limits
anthropic
Default—
Fieldprovider.allow_fallbacksTypeboolean|nullRequirementOptionalValues & limits
false, null
Default—
Method parameters and lifecycle
ParameterContract
Parametercontent_typeContractapplication/json
ParameterrequiredContractendpoint, model, requests
Parametermaterial_typesContracttext
ParameterrepresentationContractinline requests[]; each item has custom_id and body
Parameterrequest_endpoint_profileContract/v1/chat/completions
Parameterfile_materialContractCaller 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.
Parameterserialization_orderContractendpoint, model, provider (if supplied), completion_window (if supplied), requests last
Parameteroptional_controlsContractprovider.only, provider.allow_fallbacks, completion_window
Parameterschema_scopeContractText 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.

ConfigurationRate scheduleContext tokens, more thanContext tokens, up to and includingCharge
ConfigurationBase token ratesRate scheduleBase rateContext tokens, more than—Context tokens, up to and includingNo upper boundCharge
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 1Rate schedule—Context tokens, more than0Context tokens, up to and includingNo upper boundCharge
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 →

Example requests

Ailoot Ultra · Batch

curl · retained fixturePython HTTP · actual customer JSONLPython · save every completed result
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
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"))
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
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
FieldType
Fieldresults[].custom_idTypestring
Fieldresults[].response.body.choices[].message.contentTypestring|null
Fieldresults[].errorTypeobject|null
FieldusageTypeobject|null
FieldidTypestring
FieldmodelTypestring
FieldendpointTypestring
FieldstatusTypestring
Fieldrequest_countsTypeobject
Fieldresults[].idTypestring
Fieldresults[].response.status_codeTypeinteger
Fieldresults[].response.request_idTypestring
Errors and next steps
ResponseConditionNext step
Response400 · invalid_request_errorConditionInvalid documented inline envelope, duplicate keys, item identity, or configured model capabilities conflict.Next stepCorrect the indicated fields before any new submission.
Response401 · authentication_errorConditionInvalid API key.Next stepUse the authorized Ailoot key.
Response403 · permission_errorConditionBatch group unavailable.Next stepCheck key/group entitlement.
Response422 · invalid_request_errorConditionBatch uses balance billing; subscription creation is rejected.Next stepUse the authorized balance-billed group.
Response422 · price_unavailableConditionBatch input cannot be quoted.Next stepPreserve response; use documented family input.
Response402 · billing_errorConditionBatch reserve unavailable.Next stepResolve admission before a new request.
Response503 · price_unavailableConditionBatch method price/native rates unavailable.Next stepPreserve response; do not substitute prices.
Response503 · api_errorConditionExact supplier route unavailable.Next stepPreserve response for route repair.
Response503 · result_pending_checkConditionOriginal result requires checking; X-Should-Retry:false.Next stepKeep original operation_id/id and read its status; never repeat original POST.
Response404 · not_foundConditionBatch 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

Method path aliases

Use the method paths shown above.

Related caller IDs

anthropic/claude-opus-4.6:batch

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

More details

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