Gemini 2.5 Flash-Lite is Google’s stable lightweight profile for high-volume translation, classification and simple data extraction. Its hybrid reasoning can use or omit thinking according to the task. It accepts text, images, audio, video and PDF and produces text. A useful result is a category, a concise translation, a record extracted from supplied material or a bounded written explanation.
For classification, define the categories, decision rule and form of the answer. Keep the source identifier in a result when several independent items are processed. For support-message classification, classify a support message by issue type and return the sentence that supports the category. Include a rule for missing or ambiguous evidence, so a fluent answer does not fill a required field with a guess. The model’s lightweight role is most useful when the input and required result are clearly specified.
Thinking is off by default in the documented 2.5 Flash-Lite configuration. Google’s GenerateContent thinking guide allows an explicit thinking budget from 512 to 24,576 tokens, zero to keep thinking off and -1 to request dynamic thinking. Those are reasoning-budget controls, separate from the final response allowance. Enable additional reasoning when an extraction has interacting conditions or a classification has exceptions; a straightforward conversion can retain the default non-thinking behaviour. The guide notes that the model may use more or fewer thinking tokens than the requested budget.
For translation, provide the target language, audience and terms to preserve. Specify whether the result should contain only the translation or a labelled record. For document extraction, define the fields and request source passages that let the output be checked. For a recording, distinguish a transcript from a summary and identify the passage that matters. Images or video can contribute evidence for a text answer. The desired artifact should remain clear even when the input combines several media types.
The exact stable table lists function calling, code execution, file search, search grounding, Maps grounding, URL context and structured outputs. Functions need a clear purpose and defined parameters; the connected application executes the operation and supplies its result. For schema-based extraction, validate the returned structure and compare its values with the original material. A tool decision or well-formed record is useful only in the context of the source and actual returned evidence.
The native card gives a 1M context window and 64K text output. The API model page specifies 1,048,576 input tokens and 65,536 output tokens. Instructions, source content and retained conversation consume the input budget, while reasoning and a response cap affect whether the final result fits. Caching, batch, Flex and Priority processing are listed for this producer profile. For repeated tasks, retain the same category or field definitions and carry identifiers through the result so later review can locate the originating item.
This stable profile is separate from the June and September Preview variants described elsewhere in the family. The shared native card labels September Preview improvements, including instruction following and concision, specifically for that preview; they should not be silently transferred to the stable identifier. Later Flash-Lite generations also use different thinking controls and capability tables. Preserve the edition and choose the settings documented for it rather than replacing 2.5 budgets with Gemini 3 thinking-level syntax.
The card lists hallucinations and limitations in causal understanding, complex logical deduction and counterfactual reasoning, and gives a January 2025 knowledge cutoff. Supply current evidence or use a documented grounding workflow when newer facts matter. Review translations for meaning, extracted fields for source support and transcripts against the audio. A focused, small result makes this review practical without treating a polished answer as proof that the source contained the asserted detail.
", "aboutText": "Gemini 2.5 Flash-Lite is Google’s stable lightweight profile for high-volume translation, classification and simple data extraction. Its hybrid reasoning can use or omit thinking according to the task. It accepts text, images, audio, video and PDF and produces text. A useful result is a category, a concise translation, a record extracted from supplied material or a bounded written explanation.\n\nFor classification, define the categories, decision rule and form of the answer. Keep the source identifier in a result when several independent items are processed. For support-message classification, classify a support message by issue type and return the sentence that supports the category. Include a rule for missing or ambiguous evidence, so a fluent answer does not fill a required field with a guess. The model’s lightweight role is most useful when the input and required result are clearly specified.\n\nThinking is off by default in the documented 2.5 Flash-Lite configuration. Google’s GenerateContent thinking guide allows an explicit thinking budget from 512 to 24,576 tokens, zero to keep thinking off and -1 to request dynamic thinking. Those are reasoning-budget controls, separate from the final response allowance. Enable additional reasoning when an extraction has interacting conditions or a classification has exceptions; a straightforward conversion can retain the default non-thinking behaviour. The guide notes that the model may use more or fewer thinking tokens than the requested budget.\n\nFor translation, provide the target language, audience and terms to preserve. Specify whether the result should contain only the translation or a labelled record. For document extraction, define the fields and request source passages that let the output be checked. For a recording, distinguish a transcript from a summary and identify the passage that matters. Images or video can contribute evidence for a text answer. The desired artifact should remain clear even when the input combines several media types.\n\nThe exact stable table lists function calling, code execution, file search, search grounding, Maps grounding, URL context and structured outputs. Functions need a clear purpose and defined parameters; the connected application executes the operation and supplies its result. For schema-based extraction, validate the returned structure and compare its values with the original material. A tool decision or well-formed record is useful only in the context of the source and actual returned evidence.\n\nThe native card gives a 1M context window and 64K text output. The API model page specifies 1,048,576 input tokens and 65,536 output tokens. Instructions, source content and retained conversation consume the input budget, while reasoning and a response cap affect whether the final result fits. Caching, batch, Flex and Priority processing are listed for this producer profile. For repeated tasks, retain the same category or field definitions and carry identifiers through the result so later review can locate the originating item.\n\nThis stable profile is separate from the June and September Preview variants described elsewhere in the family. The shared native card labels September Preview improvements, including instruction following and concision, specifically for that preview; they should not be silently transferred to the stable identifier. Later Flash-Lite generations also use different thinking controls and capability tables. Preserve the edition and choose the settings documented for it rather than replacing 2.5 budgets with Gemini 3 thinking-level syntax.\n\nThe card lists hallucinations and limitations in causal understanding, complex logical deduction and counterfactual reasoning, and gives a January 2025 knowledge cutoff. Supply current evidence or use a documented grounding workflow when newer facts matter. Review translations for meaning, extracted fields for source support and transcripts against the audio. A focused, small result makes this review practical without treating a polished answer as proof that the source contained the asserted detail.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "fbdbc61b0013861b5fc1420b09e7dd4483f9173555c3b00f8c0e334bd3913c82", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "en", "methods": [ { "html": "google/gemini-2.5-flash-lite:batchGemini 2.5 Flash-Lite is Google’s stable multimodal text model for frequent classification, translation and simple extraction. Thinking is off by default and can be enabled with a 512–24,576-token reasoning budget. It accepts text and media, with tools, structured output and a 1,048,576-token input limit.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
Gemini 2.5 Flash-Lite is Google’s stable lightweight profile for high-volume translation, classification and simple data extraction. Its hybrid reasoning can use or omit thinking according to the task. It accepts text, images, audio, video and PDF and produces text. A useful result is a category, a concise translation, a record extracted from supplied material or a bounded written explanation.
For classification, define the categories, decision rule and form of the answer. Keep the source identifier in a result when several independent items are processed. For support-message classification, classify a support message by issue type and return the sentence that supports the category. Include a rule for missing or ambiguous evidence, so a fluent answer does not fill a required field with a guess. The model’s lightweight role is most useful when the input and required result are clearly specified.
Thinking is off by default in the documented 2.5 Flash-Lite configuration. Google’s GenerateContent thinking guide allows an explicit thinking budget from 512 to 24,576 tokens, zero to keep thinking off and -1 to request dynamic thinking. Those are reasoning-budget controls, separate from the final response allowance. Enable additional reasoning when an extraction has interacting conditions or a classification has exceptions; a straightforward conversion can retain the default non-thinking behaviour. The guide notes that the model may use more or fewer thinking tokens than the requested budget.
For translation, provide the target language, audience and terms to preserve. Specify whether the result should contain only the translation or a labelled record. For document extraction, define the fields and request source passages that let the output be checked. For a recording, distinguish a transcript from a summary and identify the passage that matters. Images or video can contribute evidence for a text answer. The desired artifact should remain clear even when the input combines several media types.
The exact stable table lists function calling, code execution, file search, search grounding, Maps grounding, URL context and structured outputs. Functions need a clear purpose and defined parameters; the connected application executes the operation and supplies its result. For schema-based extraction, validate the returned structure and compare its values with the original material. A tool decision or well-formed record is useful only in the context of the source and actual returned evidence.
The native card gives a 1M context window and 64K text output. The API model page specifies 1,048,576 input tokens and 65,536 output tokens. Instructions, source content and retained conversation consume the input budget, while reasoning and a response cap affect whether the final result fits. Caching, batch, Flex and Priority processing are listed for this producer profile. For repeated tasks, retain the same category or field definitions and carry identifiers through the result so later review can locate the originating item.
This stable profile is separate from the June and September Preview variants described elsewhere in the family. The shared native card labels September Preview improvements, including instruction following and concision, specifically for that preview; they should not be silently transferred to the stable identifier. Later Flash-Lite generations also use different thinking controls and capability tables. Preserve the edition and choose the settings documented for it rather than replacing 2.5 budgets with Gemini 3 thinking-level syntax.
The card lists hallucinations and limitations in causal understanding, complex logical deduction and counterfactual reasoning, and gives a January 2025 knowledge cutoff. Supply current evidence or use a documented grounding workflow when newer facts matter. Review translations for meaning, extracted fields for source support and transcripts against the audio. A focused, small result makes this review practical without treating a polished answer as proof that the source contained the asserted detail.
POST /v1/batchestexttext| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldendpoint | Typestring | RequirementRequired | Values & limits /v1/chat/completions | Default— |
Fieldmodel | Typestring | RequirementRequired | Values & limits google/gemini-2.5-flash-lite: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 google/gemini-2.5-flash-lite:batch, google/gemini-2.5-flash-lite | Default— |
Fieldprovider.only | Typestring[] | RequirementOptional | Values & limits google-ai-studio | Default— |
Fieldprovider.allow_fallbacks | Typeboolean|null | RequirementOptional | Values & limits false, null | Default— |
| 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
Tariff references do not add request options. Supported parameters are listed for the selected method.
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 $0.0001 / 1K tokens Output · Output tokens $0.0004 / 1K tokens Input · Cache read $0.00002 / 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 includingNo upper bound | Charge Input · Input tokens $0.0001 / 1K tokens Output · Output tokens $0.0004 / 1K tokens Input · Cache read $0.00002 / 1K tokens Input · Cache write — / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\npython3 - <<'PY_REQUEST'\nimport json\nfrom pathlib import Path\nbody=json.loads('{"endpoint":"/v1/chat/completions","model":"google/gemini-2.5-flash-lite:batch","requests":[{"custom_id":"req-0001","body":{"messages":[{"role":"user","content":"Hello!"}],"max_tokens":16}}]}')\nPath("batch-request.json").write_text(json.dumps(body,ensure_ascii=False),encoding="utf-8")\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/batches \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @batch-request.json -D batch-response-headers.txt -o batch-create-response.json\nimport json, os\nfrom pathlib import Path\nfrom urllib.request import Request, urlopen\n\ndef prepare_requests(customer_path):\n path = Path(customer_path)\n if not path.is_file(): raise ValueError("Customer JSONL file is missing")\n items = [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()]\n if not items: raise ValueError("Customer JSONL contains no requests")\n ids = set()\n for item in items:\n if set(item) != {"custom_id", "body"}: raise ValueError("Each item needs custom_id and body")\n cid = item["custom_id"]\n if not isinstance(cid, str) or not cid.strip() or cid in ids: raise ValueError("custom_id must be nonempty and unique")\n ids.add(cid)\n if not isinstance(item["body"], dict) or not item["body"].get("messages"): raise ValueError("Supply actual text messages")\n supplied_model = item["body"].get("model")\n if supplied_model is not None and supplied_model not in ['google/gemini-2.5-flash-lite:batch', 'google/gemini-2.5-flash-lite']: raise ValueError("body.model must be an exact documented caller or wire ID")\n return {"endpoint":"/v1/chat/completions", "model":"google/gemini-2.5-flash-lite:batch", "requests":items}\n\nif __name__ == "__main__":\n material = os.environ.get("AILOOT_BATCH_REQUESTS_JSONL", "")\n if not material: raise SystemExit("Set AILOOT_BATCH_REQUESTS_JSONL to your actual customer file")\n body = prepare_requests(material)\n key = os.environ.get("AILOOT_API_KEY", "")\n if not key: raise SystemExit("Set AILOOT_API_KEY")\n 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")\n with urlopen(request) as response:\n raw = response.read()\n Path("batch-create-response.json").write_bytes(raw)\n print(raw.decode("utf-8"))\nimport json\nfrom pathlib import Path\nraw = Path("batch-status-response.json").read_bytes()\nresponse = json.loads(raw)\nif response.get("status") != "completed":\n raise SystemExit("Keep the original operation; read its status without resubmitting")\nresults = response.get("results")\nif not isinstance(results, list) or not results:\n raise SystemExit("Preserve the original response; completed results are missing")\nPath("batch-results.jsonl").write_text("".join(json.dumps(item, ensure_ascii=False) + "\\n" for item in results), encoding="utf-8")\n# Preserve batch-status-response.json with aggregate usage and every result/error.\ninline results[].response.body JSON
GET /v1/batches/{operation_id}set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nBATCH_OPERATION_ID="$(python3 - <<'PY_ID'\nimport json\nfrom pathlib import Path\nfrom urllib.parse import quote\nresponse = json.loads(Path("batch-create-response.json").read_text(encoding="utf-8"))\noperation = response.get("id")\nif not isinstance(operation, str) or not operation: raise SystemExit("No actual original operation ID; preserve the response and do not resubmit")\nprint(quote(operation, safe=""))\nPY_ID\n)"\ncurl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/batches/$BATCH_OPERATION_ID" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o batch-status-response.json\nKeep 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.
Preserve the original operation ID. 503 result_pending_check has X-Should-Retry:false; never resubmit an unknown original batch.
| 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 |
| 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. |
Ailoot Ultra google/gemini-2.5-flash-lite:batch
Use the method paths shown above.