models

Google: Gemini 3.6 Flash (batch)

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Google: Gemini 3.6 Flash (batch)

Gemini 3.6 Flash is Google’s multimodal text model for coding, spatial analysis and multi-step agents. It emphasizes diagnostic inspection, focused edits and fewer unnecessary execution loops. It accepts text, images, audio, video and PDF, with tools, structured output and a 1,048,576-token input limit.

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

Gemini 3.6 Flash is Google’s multimodal workhorse profile for coding, knowledge work and agentic execution. It builds on Gemini 3.5 Flash, with a focus on improved multimodal performance and token efficiency. The model accepts text, images, audio, video and PDF and returns text. A useful assignment can combine code, a screenshot and a requirement, or compare a chart or visual plan with written constraints to produce a checked explanation or targeted revision.

The developer guide emphasizes fewer unnecessary reasoning steps, turns and tool calls in multi-step work, along with more focused edits. For diagnosis, provide the observed failure, the relevant source and the behaviour that should remain unchanged. For chart debugging, ask the model to inspect why a chart renders the wrong series, identify the data transformation involved and propose one correction while retaining the surrounding layout. The result can then be compared with the actual input data and the required chart behaviour.

Upfront programmatic inspection is a distinctive behaviour described for 3.6. The maker says the model more often inspects a problem with diagnostic code before making changes. This can help a complex investigation, but the guide notes that it can add exploratory steps to routine frontend work. State whether the task needs an investigation, a simple edit or a design comparison. Supply the information that makes that distinction clear and specify the permitted actions for the connected application’s tools.

Spatial and multimodal reasoning are also highlighted: chart interpretation, visual blueprint conversion and multi-element web layouts. Supply the relevant view or pages, identify what should be interpreted and ask for the evidence behind the conclusion. For a design task, include concrete layout and styling guidelines. The maker notes a functional-code emphasis and that evaluators sometimes preferred earlier models’ visual styling, making an explicit visual brief useful. Check the result against the actual diagram or design requirements.

Medium is the documented default thinking level. Google’s model-specific thinking table lists minimal, low, medium and high; the 3.6 migration guide uses medium or high in its effort examples. The exact page lists function calling, code execution, file search, search grounding, Maps grounding, URL context and structured outputs, with Computer Use as a preview capability. Define function inputs and the required result clearly. A function selected by the model needs a real application result before a later answer can rely on its outcome. For a structured analysis, define the schema and source evidence needed for each finding.

The 3.6 guide changes preparation compared with earlier Gemini requests. It deprecates temperature, top-p and top-k sampling settings, rejects a prefilled final model-role turn and recommends system instructions or structured outputs for controlling the answer. Its function-response rules match a response to its call by identity and name, and the Gemini 3 baseline preserves thought signatures in multi-turn use. A practical continuation should carry the unmodified relevant history and tool result rather than imitate a previous answer prefix.

The native card specifies up to 1M input context and 64K text output; the exact API table gives 1,048,576 input tokens and 65,536 output tokens. Budget the instructions, history and media as part of the input, and ask for an output sized for the task. The producer page also lists caching, batch, Flex and Priority processing. When processing independent records, keep the record identifier and result format explicit. The output is a text artifact, even when the evidence includes photographs, audio or video.

Possible limitations include hallucinations and occasional slowness or timeouts. Its March 2026 cutoff includes domains whose knowledge remains limited to January 2025, so attach newer material or use a documented grounding workflow when current facts matter. Review calculations, source references, visual interpretations and proposed modifications. The distinctive preparation for this edition is a focused diagnostic brief, clear tool scope and explicit design constraints, followed by inspection of the concrete result.

Ailoot Ultra · Batch POST /v1/batches google/gemini-3.6-flash:batch

google/gemini-3.6-flash:batch

Google /google/gemini-3.6-flash:batch

Overview

Gemini 3.6 Flash is Google’s multimodal text model for coding, spatial analysis and multi-step agents. It emphasizes diagnostic inspection, focused edits and fewer unnecessary execution loops. It accepts text, images, audio, video and PDF, with tools, structured output and a 1,048,576-token input limit.

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
google/gemini-3.6-flash: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
google/gemini-3.6-flash:batch, google/gemini-3.6-flash
Default—
Fieldprovider.onlyTypestring[]RequirementOptionalValues & limits
google-vertex/global
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
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.

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 $0.00075 / 1K tokens
Output · Output tokens $0.00375 / 1K tokens
Input · Cache read $0.000075 / 1K tokens
Input · Cache write $0.0000833333333333334 / 1K tokens
Input · Cache write, 1 hour — / 1K tokens
ConfigurationRequest-length tier 1Rate schedule—Context tokens, more than0Context tokens, up to and includingNo upper boundCharge
Input · Input tokens $0.00075 / 1K tokens
Output · Output tokens $0.00375 / 1K tokens
Input · Cache read $0.000075 / 1K tokens
Input · Cache write $0.0000833333333333334 / 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

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":"google/gemini-3.6-flash: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 ['google/gemini-3.6-flash:batch', 'google/gemini-3.6-flash']: raise ValueError("body.model must be an exact documented caller or wire ID")
    return {"endpoint":"/v1/chat/completions", "model":"google/gemini-3.6-flash: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 google/gemini-3.6-flash:batch

Method path aliases

Use the method paths shown above.

Related caller IDs

google/gemini-3.6-flash:batch

FAQ · Google: Gemini 3.6 Flash (batch)
What inputs and results are available?

POST /v1/batches · google/gemini-3.6-flash:batch: text → text

Which fields does the request use?

POST /v1/batches · google/gemini-3.6-flash:batch: endpoint, model, requests, completion_window, provider

What limits apply?

POST /v1/batches · google/gemini-3.6-flash:batch: requests.min_items: 1

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