SpaceXAI: Grok 4.3 (batch)
Grok 4.3 is a text-and-image model for instruction-driven work, reasoning and tool-connected tasks, with a 1,000,000-token context. It provides function calling, structured output and selectable reasoning effort in the producer’s documented configuration.
About the model
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
Grok 4.3 is the producer’s general-purpose model emphasizing instruction following and tool use. Its model card accepts text and images, generates text and specifies a 1,000,000-token context window. The listed capabilities include function calling, structured outputs and configurable reasoning, with batch processing supported in the manufacturer’s service.
The current detailed model specification lists none, low, medium, high and xhigh reasoning effort, with low as the default. None skips the reasoning stage; the other choices allocate thinking before the answer. These are settings of the exact producer model card, distinct from the effort lists and defaults of later Grok releases.
For long-document analysis, provide the relevant material and define the sections or findings the answer should return. The context can hold a large working set, but the task still benefits from priorities and an explicit deliverable. Ask for the conclusion, the supporting passage and any unresolved condition instead of treating a long context as a substitute for a clear question.
For visual material, identify the object, chart feature or page detail to inspect and explain how it relates to the written task. A useful result ties the observation to the question. If a conclusion also depends on external information, provide that evidence separately so the model can distinguish what the image shows from what another source establishes.
In a function-based workflow, the model generates a proposed call from the tool definitions. The application executes the function and returns the result. Keep the function’s inputs, the returned observation and the next model step connected. For a code or data task, request a result that states what was proposed and what the application actually observed.
Structured output can turn a document extraction or analytical report into defined fields. The producer’s schema support covers common data types and bounded constraints, while some advanced constraints depend on model behavior. Give each field a clear meaning and validate the result against the application’s needs. A schema-shaped result still needs evidence for its content; a proposed action still needs execution by the surrounding workflow.
Ailoot Ultra · Batch POST /v1/batches x-ai/grok-4.3:batch
x-ai/grok-4.3:batchOverview
Grok 4.3 is a text-and-image model for instruction-driven work, reasoning and tool-connected tasks, with a 1,000,000-token context. It provides function calling, structured output and selectable reasoning effort in the producer’s documented configuration.
- 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 |
|---|---|---|---|---|
Fieldendpoint | Typestring | RequirementRequired | Values & limits /v1/chat/completions | Default— |
Fieldmodel | Typestring | RequirementRequired | Values & limits x-ai/grok-4.3:batch | Default— |
Fieldrequests | Typebatch_item[] | RequirementRequired | Values & limits Minimum items: 1 | Default— |
Fieldrequests[].custom_id | Typestring | RequirementRequired | Values & limits | Default— |
Fieldrequests[].body.messages | Typemessage[] | RequirementRequired | Values & limits | Default— |
Fieldcompletion_window | Typestring | RequirementOptional | Values & limits 24h | Default— |
Fieldprovider | Typeobject|null | RequirementOptional | Values & limits | Default— |
Fieldrequests[].body.model | Typestring | RequirementOptional | Values & limits x-ai/grok-4.3:batch, x-ai/grok-4.3 | Default— |
Fieldprovider.only | Typestring[] | RequirementOptional | Values & limits xai | Default— |
Fieldprovider.allow_fallbacks | Typeboolean|null | RequirementOptional | Values & limits false, null | Default— |
Method parameters and lifecycle
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractendpoint, model, requests |
Parametermaterial_types | Contracttext |
Parameterrepresentation | Contractinline requests[]; each item has custom_id and body |
Parameterrequest_endpoint_profile | Contract/v1/chat/completions |
Parameterfile_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. |
Parameterserialization_order | Contractendpoint, model, provider (if supplied), completion_window (if supplied), requests last |
Parameteroptional_controls | Contractprovider.only, provider.allow_fallbacks, completion_window |
Parameterschema_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 $0.004 / 1K tokens Input · Cache read $0.00032 / 1K tokens Input · Cache write — / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
| ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens $0.002 / 1K tokens Output · Output tokens $0.004 / 1K tokens Input · Cache read $0.00032 / 1K tokens Input · Cache write — / 1K tokens Input · Cache write, 1 hour — / 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 $0.004 / 1K tokens Output · Output tokens $0.008 / 1K tokens Input · Cache read $0.00064 / 1K tokens Input · Cache write — / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
Example requests
Ailoot Ultra · Batch
set -eu
: "${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":"x-ai/grok-4.3: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 ['x-ai/grok-4.3:batch', 'x-ai/grok-4.3']: raise ValueError("body.model must be an exact documented caller or wire ID")
return {"endpoint":"/v1/chat/completions", "model":"x-ai/grok-4.3: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
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 |
|---|---|
Fieldresults[].custom_id | Typestring |
Fieldresults[].response.body.choices[].message.content | Typestring|null |
Fieldresults[].error | Typeobject|null |
Fieldusage | Typeobject|null |
Fieldid | Typestring |
Fieldmodel | Typestring |
Fieldendpoint | Typestring |
Fieldstatus | Typestring |
Fieldrequest_counts | Typeobject |
Fieldresults[].id | Typestring |
Fieldresults[].response.status_code | Typeinteger |
Fieldresults[].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 x-ai/grok-4.3:batch
Method path aliases
Use the method paths shown above.
Related caller IDs
FAQ · SpaceXAI: Grok 4.3 (batch)
- What inputs and results are available?
POST /v1/batches·x-ai/grok-4.3:batch:text→text- Which fields does the request use?
POST /v1/batches·x-ai/grok-4.3:batch:endpoint,model,requests,completion_window,provider- What limits apply?
POST /v1/batches·x-ai/grok-4.3:batch:requests.min_items:1