Source: https://ailoot.ai/models/en/openai-gpt-6-luna-pro/ Canonical: https://ailoot.ai/models/en/openai-gpt-6-luna-pro/ Language: en # OpenAI: GPT-6 Luna Pro [Markdown](https://ailoot.ai/models/en/openai-gpt-6-luna-pro/index.md) · [JSON](https://ailoot.ai/models/en/openai-gpt-6-luna-pro/facts.json) ## [OpenAI: GPT-6 Luna Pro](https://ailoot.ai/models/en/openai-gpt-6-luna-pro/) GPT-6 Luna with Pro reasoning for focused tasks that need additional analysis before a final answer. The base model accepts text and images, making it useful for rule-based document handling, visual questions and concise written results. - [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/openai-gpt-6-luna-pro/#method-0) - [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/openai-gpt-6-luna-pro/#method-1) - [**Ailoot Ultra · OpenAI Responses** `POST /v1/responses` `openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/openai-gpt-6-luna-pro/#method-2) About the model This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below. GPT-6 Luna Pro denotes OpenAI’s GPT-6 Luna with Pro reasoning. Luna is designed for focused tasks and high-volume workloads; its inputs are text and images and its output is text. Pro adds model work when developing the final answer. It is an execution mode applied to the chosen base model, distinct from the reasoning-effort setting that controls the amount of analysis within that mode. A practical application is processing a narrowly defined request with several rules or exceptions. Supply the request, the categories it may belong to and the information that determines the next action. Ask for the category, the relevant facts and a short proposed response. An illustrative task is to classify a document request, identify a missing field and draft a message asking for that field. The task remains focused even when its conditions require careful consideration. For an image-based question, provide a clear screenshot or other visual material and identify the detail to inspect. You can request an explanation of a visible interface state together with a short instruction for the reader. For written material, define the fields or statements that must survive the transformation, the allowed categories and the expected answer format. A small set of representative examples can clarify the boundary between similar categories without making the model infer your rules. OpenAI specifies a 1,050,000-token context window for GPT-6 Luna, with a maximum input of 922,000 tokens and a maximum output of 128,000 tokens. The documented knowledge cutoff is May 18, 2026. The base model supports none, low, medium, high, xhigh and max reasoning effort, with medium as the default. Reasoning occupies token space as well as the final answer, so the task brief and supplied material should leave room for analysis and the requested result. The producer documents Pro in the Responses API for difficult requests that allow additional latency and model activity. GPT-6 Luna’s built-in tools and reasoning with function calls use Responses; in the producer’s Chat Completions interface, function calling is supported only with reasoning effort set to none. The base model lists streaming, Structured Outputs, web and file search, function calling and prompt caching. Its tool set also includes image generation, code interpretation, shell and patch operations, skills, computer use, MCP connections and tool search. Your application determines and executes the operations it exposes. Use a precise output contract for the final task: the decision, the fields supporting it and any information still missing. For example, ask for one category, a brief justification tied to the supplied rule and the next question to send to the reader. Review the result against those rules rather than adding an unrestricted discussion. This workflow uses Luna’s focused-task role while reserving Pro’s extra work for a request whose dependencies or exceptions need fuller examination. Practical task ### Find missing request details Technical example in English ``` Find missing request details Process this equipment request using the supplied rules. Every request needs item, quantity and delivery site. Urgent requests also need a reason. Message: "Urgent: please send 4 replacement keyboards." Return the supplied fields, missing required fields and a brief reply asking only for the missing details. Do not invent a site or urgency reason. ``` #### Expected result ``` A compact field table, missing-field list and targeted clarification message. ``` #### Check the result ``` Check that quantity four and keyboards are retained, while delivery site and urgent reason stay missing. ``` **Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `openai/gpt-6-luna-pro` [`openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-luna-pro&route=Ultra&caller=openai%2Fgpt-6-luna-pro&fmt=chat) OpenAI /`openai/gpt-6-luna-pro` ### Overview GPT-6 Luna with Pro reasoning for focused tasks that need additional analysis before a final answer. The base model accepts text and images, making it useful for rule-based document handling, visual questions and concise written results. Accepted inputs Text Results Text ### Available in Ailoot · inputs & methods **Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` Input types `text` Output types `text` Output format json or SSE | Field | Type | Requirement | Values & limits | Default | | --- | --- | --- | --- | --- | | Field`model` | Type`string` | RequirementRequired | Values & limits openai/gpt-6-luna-pro | Default— | | Field`messages` | Type`message[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— | | Field`messages[].role` | Type`string` | RequirementRequired | Values & limits Examples: system, user, assistant, tool, function Conditions: These roles are explicitly represented by Source compatibility types; the exact model role set remains model-specific. Model-specific | Default— | | Field`messages[].content` | Type`string\|content_part[]\|null` | RequirementOptional | Values & limits | Default— | | Field`messages[].tool_calls` | Type`tool_call[]` | RequirementOptional | Values & limits | Default— | | Field`messages[].tool_call_id` | Type`string` | RequirementOptional | Values & limits Applies when: role=tool; use actual returned ID | Default— | | Field`messages[].name` | Type`string` | RequirementOptional | Values & limits | Default— | | Field`messages[].reasoning_content` | Type`string` | RequirementOptional | Values & limits Applies when: Round-trip actual returned reasoning where this model uses it | Default— | | Field`messages[].reasoning_details` | Type`object\|array` | RequirementOptional | Values & limits Model-specific | Default— | | Field`max_tokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— | | Field`max_completion_tokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— | | Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse | | Field`stream_options.include_usage` | Type`boolean` | RequirementOptional | Values & limits Model-specific | Default— | | Field`temperature` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— | | Field`top_p` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— | | Field`stop` | Type`string\|string[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`tools` | Type`function_tool[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`tools[].type` | Type`string` | RequirementOptional | Values & limits function Model-specific | Default— | | Field`tools[].function.name` | Type`string` | RequirementRequired | Values & limits Applies when: function tool supplied | Default— | | Field`tools[].function.description` | Type`string` | RequirementOptional | Values & limits | Default— | | Field`tools[].function.parameters` | Type`JSON_schema` | RequirementOptional | Values & limits | Default— | | Field`tool_choice` | Type`string\|object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`parallel_tool_calls` | Type`boolean` | RequirementOptional | Values & limits Model-specific | Default— | | Field`response_format` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`reasoning_effort` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`reasoning` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`service_tier` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`instructions` | Type`string` | RequirementOptional | Values & limits Compatibility field | Default— | | Field`functions` | Type`function[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`function_call` | Type`string\|object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`prompt_cache_options` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`modalities` | Type`string[]` | RequirementOptional | Values & limits text | Default— | | Field`provider` | Type`object` | RequirementOptional | Values & limits Conditions: provider.options is rejected on this Ultra text route | Default— | | Field`cache_control.ttl` | Type`string` | RequirementOptional | Values & limits Conditions: 1h is rejected in actual prompt-cache locations | Default— | Input material combinations **Text** · UTF8 text `messages[].content` Method parameters and lifecycle | Parameter | Contract | | --- | --- | | Parameter`content_type` | Contractapplication/json | | Parameter`required` | Contractmodel, messages | | Parameter`material_types` | Contracttext | | Parameter`messages` | Contractmessage array with role/content shape | | Parameter`file_material` | Contractactual UTF-8 document inserted as literal text; no file ID inferred | | Parameter`optional_controls` | Contractstream, temperature, top\_p, stop, max\_tokens, max\_completion\_tokens, reasoning, response\_format, tools, tool\_choice | | Parameter`control_scope` | Contractmodel-specific; user function tools differ from hosted tools | | Parameter`output_modalities` | Contracttext | | Parameter`hosted_operations` | Contractfalse | | Parameter`multimodal_input_binding` | Contractnull | Lifecycle: `synchronous_or_streamed` Send exact model ID with messages. Context length is not an output cap. A text file may supply literal text; image/audio/file-object inputs need exact binding. ### Pricing Tariff references do not add request options. Supported parameters are listed for the selected method. Fast mode Standard rate When fast mode is selected Flex mode Standard rate When flex mode is selected Maximum reasoning effort Standard rate When maximum reasoning effort uses the default adjustment Reasoning effort · high Standard rate When reasoning effort is high Reasoning effort · low Standard rate When reasoning effort is low Reasoning effort · max Standard rate When reasoning effort is max Reasoning effort · medium Standard rate When reasoning effort is medium Reasoning effort · none Standard rate When reasoning effort is none Reasoning effort · xhigh Standard rate When reasoning effort is xhigh #### 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 **$0.0002** / 1K tokens Output · Output tokens **$0.001** / 1K tokens Input · Cache read **$0.00002** / 1K tokens Input · Cache write **$0.00025** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | | ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including272,000 | Charge Input · Input tokens **$0.0002** / 1K tokens Output · Output tokens **$0.001** / 1K tokens Input · Cache read **$0.00002** / 1K tokens Input · Cache write **$0.00025** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | | ConfigurationRequest-length tier 2 | Rate schedule— | Context tokens, more than272,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0004** / 1K tokens Output · Output tokens **$0.0015** / 1K tokens Input · Cache read **$0.00004** / 1K tokens Input · Cache write **$0.0005** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/) ### Example requests #### Ailoot Ultra · OpenAI Chat curlPython SDKPython stream ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "openai/gpt-6-luna-pro", "messages": [{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}]}') Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \ -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path r=json.loads(Path("result.json").read_text()) for x in r.get("choices",[]): if x.get("message",{}).get("content"): print(x["message"]["content"]) PY_RESULT ``` ```python from openai import OpenAI import os if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0) result=client.chat.completions.create(model='openai/gpt-6-luna-pro',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(result.to_dict(mode="json")) ``` ```python from openai import OpenAI import os from pathlib import Path if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) with client.chat.completions.stream(model='openai/gpt-6-luna-pro',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream: with Path("stream-events.jsonl").open("w",encoding="utf-8") as log: for event in stream: payload=event.to_dict(mode="json") log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush() print(json.dumps(payload,ensure_ascii=False)) final=stream.get_final_completion() save_result(final.to_dict(mode="json"),"stream-result") ``` ### Receive and save results #### Ailoot Ultra · OpenAI Chat json or SSE ##### Keep all completed results Keep every complete returned response, file and content part. Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage. ##### If the original response needs checking Keep request/response IDs and headers. No generic text job retrieval URL is supplied. Response fields | Field | Type | | --- | --- | | Field`choices[].index` | Typeinteger | | Field`choices[].message.content` | Typestring\|null | | Field`choices[].message.tool_calls` | Typetool\_call\[\] | | Field`choices[].message.reasoning_content` | Typestring | | Field`choices[].message.reasoning_details` | Typeobject\|array | | Field`choices[].finish_reason` | Typestring\|null | | Field`usage` | Typeobject | Errors and next steps | Response | Condition | Next step | | --- | --- | --- | | Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. | ### Aliases #### Model aliases **Ailoot Ultra** [`openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-luna-pro&route=Ultra&caller=openai%2Fgpt-6-luna-pro&fmt=chat) #### Method path aliases Use the method paths shown above. #### Related caller IDs [`openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-luna-pro&route=Ultra&caller=openai%2Fgpt-6-luna-pro&fmt=chat) **Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `openai/gpt-6-luna-pro` [`openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-luna-pro&route=Ultra&caller=openai%2Fgpt-6-luna-pro&fmt=messages) OpenAI /`openai/gpt-6-luna-pro` ### Overview GPT-6 Luna with Pro reasoning for focused tasks that need additional analysis before a final answer. The base model accepts text and images, making it useful for rule-based document handling, visual questions and concise written results. Accepted inputs Text Results Text ### Available in Ailoot · inputs & methods **Ailoot Ultra · Anthropic Messages** `POST /v1/messages` Input types `text` Output types `text` Output format json or SSE | Field | Type | Requirement | Values & limits | Default | | --- | --- | --- | --- | --- | | Field`model` | Type`string` | RequirementRequired | Values & limits openai/gpt-6-luna-pro | Default— | | Field`messages` | Type`message[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— | | Field`messages[].role` | Type`string` | RequirementRequired | Values & limits user, assistant | Default— | | Field`messages[].content` | Type`string\|content_block[]` | RequirementRequired | Values & limits | Default— | | Field`system` | Type`string\|content_block[]` | RequirementOptional | Values & limits | Default— | | Field`max_tokens` | Type`integer` | RequirementRequired | Values & limits Minimum: 1 Limit applies to: exact selected model/card ceiling | Default— | | Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse | | Field`temperature` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— | | Field`top_p` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— | | Field`stop_sequences` | Type`string[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`tools` | Type`tool[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`tools[].name` | Type`string` | RequirementOptional | Values & limits Applies when: tool supplied | Default— | | Field`tools[].description` | Type`string` | RequirementOptional | Values & limits | Default— | | Field`tools[].input_schema` | Type`JSON_schema` | RequirementOptional | Values & limits | Default— | | Field`tool_choice` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`thinking.type` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`thinking.budget_tokens` | Type`integer` | RequirementOptional | Values & limits Model-specific | Default— | | Field`output_config.effort` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`metadata` | Type`object` | RequirementOptional | Values & limits | Default— | | Field`cache_control` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | Input material combinations **Text** · UTF8 text `messages[].content or type=text block` **Text + image** `{type:image,source:{type:base64,media_type,data}} or source type=url` Method parameters and lifecycle | Parameter | Contract | | --- | --- | | Parameter`material_types` | Contracttext | | Parameter`required` | Contractmodel, messages, max\_tokens | | Parameter`optional_controls` | Contractnull | | Parameter`content_type` | Contractapplication/json | | Parameter`text_file_material` | ContractRead the actual UTF-8 document and put its text in the indicated input or message content string. | Lifecycle: `exact retained published method` Send the exact model ID and required fields. Keep every returned item and its original identifiers. ### Pricing Tariff references do not add request options. Supported parameters are listed for the selected method. Fast mode Standard rate When fast mode is selected Flex mode Standard rate When flex mode is selected Maximum reasoning effort Standard rate When maximum reasoning effort uses the default adjustment Reasoning effort · high Standard rate When reasoning effort is high Reasoning effort · low Standard rate When reasoning effort is low Reasoning effort · max Standard rate When reasoning effort is max Reasoning effort · medium Standard rate When reasoning effort is medium Reasoning effort · none Standard rate When reasoning effort is none Reasoning effort · xhigh Standard rate When reasoning effort is xhigh #### 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 **$0.0002** / 1K tokens Output · Output tokens **$0.001** / 1K tokens Input · Cache read **$0.00002** / 1K tokens Input · Cache write **$0.00025** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | | ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including272,000 | Charge Input · Input tokens **$0.0002** / 1K tokens Output · Output tokens **$0.001** / 1K tokens Input · Cache read **$0.00002** / 1K tokens Input · Cache write **$0.00025** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | | ConfigurationRequest-length tier 2 | Rate schedule— | Context tokens, more than272,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0004** / 1K tokens Output · Output tokens **$0.0015** / 1K tokens Input · Cache read **$0.00004** / 1K tokens Input · Cache write **$0.0005** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/) ### Example requests #### Ailoot Ultra · Anthropic Messages Complete minimal JSON bodycurl · use your UTF-8 documentPython · save the complete result ```json { "model": "openai/gpt-6-luna-pro", "max_tokens": 4096, "messages": [ { "role": "user", "content": "Summarize the incident report." } ] } ``` ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}" export AILOOT_TEXT_FILE python3 - <<'PY_REQUEST' import json, os from pathlib import Path source_file = Path(os.environ['AILOOT_TEXT_FILE']) if not source_file.is_file(): raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document') text = source_file.read_text(encoding='utf-8') if not text.strip(): raise SystemExit('Choose a document containing text') payload = {'model': 'openai/gpt-6-luna-pro', 'max_tokens': 4096, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]} payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text Path('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8') PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \ -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path result = json.loads(Path('result.json').read_text(encoding='utf-8')) print(json.dumps(result, ensure_ascii=False, indent=2)) PY_RESULT ``` ```python import json, os from pathlib import Path source_file = Path(os.environ['AILOOT_TEXT_FILE']) if not source_file.is_file(): raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document') text = source_file.read_text(encoding='utf-8') if not text.strip(): raise SystemExit('Choose a document containing text') payload = {'model': 'openai/gpt-6-luna-pro', 'max_tokens': 4096, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]} payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text from urllib.request import Request, urlopen from urllib.error import HTTPError api_key = os.environ['AILOOT_API_KEY'] if not api_key.strip(): raise SystemExit('Set AILOOT_API_KEY before making a request') headers = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'} headers['x-api-key'] = api_key request = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST') try: with urlopen(request, timeout=120) as response: raw = response.read() Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8') except HTTPError as error: Path('result.json').write_bytes(error.read()) Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8') raise Path('result.json').write_bytes(raw) import json from pathlib import Path result = json.loads(Path('result.json').read_text(encoding='utf-8')) print(json.dumps(result, ensure_ascii=False, indent=2)) ``` ### Receive and save results #### Ailoot Ultra · Anthropic Messages json or SSE ##### Keep all completed results Keep every complete returned response, file and content part. Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output. ##### If the original response needs checking Keep request/response IDs and headers. No generic text job retrieval URL is supplied. Response fields | Field | Type | | --- | --- | | Field`id` | Typestring | | Field`model` | Typestring | | Field`content[]` | Typetext\|thinking\|tool\_use\|other content block | | Field`stop_reason` | Typestring\|null | | Field`usage` | Typeobject | Errors and next steps | Response | Condition | Next step | | --- | --- | --- | | Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. | ### Aliases #### Model aliases **Ailoot Ultra** [`openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-luna-pro&route=Ultra&caller=openai%2Fgpt-6-luna-pro&fmt=messages) #### Method path aliases Use the method paths shown above. #### Related caller IDs [`openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-luna-pro&route=Ultra&caller=openai%2Fgpt-6-luna-pro&fmt=messages) **Ailoot Ultra · OpenAI Responses** `POST /v1/responses` `openai/gpt-6-luna-pro` [`openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-luna-pro&route=Ultra&caller=openai%2Fgpt-6-luna-pro&fmt=responses) OpenAI /`openai/gpt-6-luna-pro` ### Overview GPT-6 Luna with Pro reasoning for focused tasks that need additional analysis before a final answer. The base model accepts text and images, making it useful for rule-based document handling, visual questions and concise written results. Accepted inputs Text Results Text ### Available in Ailoot · inputs & methods **Ailoot Ultra · OpenAI Responses** `POST /v1/responses` Input types `text` Output types `text` Output format json or SSE | Field | Type | Requirement | Values & limits | Default | | --- | --- | --- | --- | --- | | Field`model` | Type`string` | RequirementRequired | Values & limits openai/gpt-6-luna-pro | Default— | | Field`input` | Type`string\|input_item[]` | RequirementRequired | Values & limits | Default— | | Field`instructions` | Type`string` | RequirementOptional | Values & limits | Default— | | Field`input[].type` | Type`string` | RequirementOptional | Values & limits message, reasoning, function\_call, function\_call\_output | Default— | | Field`input[].content` | Type`string\|content_part[]` | RequirementOptional | Values & limits | Default— | | Field`input[].call_id` | Type`string` | RequirementOptional | Values & limits Applies when: function\_call\_output; retain actual returned call\_id | Default— | | Field`input[].output` | Type`string\|content_part[]` | RequirementOptional | Values & limits Applies when: function\_call\_output | Default— | | Field`max_output_tokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— | | Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse | | Field`temperature` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— | | Field`top_p` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— | | Field`tools` | Type`tool[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`tool_choice` | Type`string\|object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`parallel_tool_calls` | Type`boolean` | RequirementOptional | Values & limits Model-specific | Default— | | Field`reasoning.effort` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`reasoning.summary` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`text.format` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | | Field`text.verbosity` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`include` | Type`string[]` | RequirementOptional | Values & limits Model-specific | Default— | | Field`store` | Type`boolean` | RequirementOptional | Values & limits Model-specific | Default— | | Field`previous_response_id` | Type`string` | RequirementNot supported | Values & limits ID requirement: Only an actual response ID from a supported continuation Conditions: Replay the actual conversation history with each request. | Default— | | Field`service_tier` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`prompt_cache_key` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— | | Field`prompt_cache_options` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— | Input material combinations **Text** · UTF8 text `input text or input_text part` **Text + image** `{type:input_image,image_url}` Method parameters and lifecycle | Parameter | Contract | | --- | --- | | Parameter`material_types` | Contracttext | | Parameter`required` | Contractmodel, input | | Parameter`optional_controls` | Contractnull | | Parameter`content_type` | Contractapplication/json | | Parameter`text_file_material` | ContractRead the actual UTF-8 document and put its text in the indicated input or message content string. | Lifecycle: `exact retained published method` Send the exact model ID and required fields. Keep every returned item and its original identifiers. ### Pricing Tariff references do not add request options. Supported parameters are listed for the selected method. Fast mode Standard rate When fast mode is selected Flex mode Standard rate When flex mode is selected Maximum reasoning effort Standard rate When maximum reasoning effort uses the default adjustment Reasoning effort · high Standard rate When reasoning effort is high Reasoning effort · low Standard rate When reasoning effort is low Reasoning effort · max Standard rate When reasoning effort is max Reasoning effort · medium Standard rate When reasoning effort is medium Reasoning effort · none Standard rate When reasoning effort is none Reasoning effort · xhigh Standard rate When reasoning effort is xhigh #### 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 **$0.0002** / 1K tokens Output · Output tokens **$0.001** / 1K tokens Input · Cache read **$0.00002** / 1K tokens Input · Cache write **$0.00025** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | | ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including272,000 | Charge Input · Input tokens **$0.0002** / 1K tokens Output · Output tokens **$0.001** / 1K tokens Input · Cache read **$0.00002** / 1K tokens Input · Cache write **$0.00025** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | | ConfigurationRequest-length tier 2 | Rate schedule— | Context tokens, more than272,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0004** / 1K tokens Output · Output tokens **$0.0015** / 1K tokens Input · Cache read **$0.00004** / 1K tokens Input · Cache write **$0.0005** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/) ### Example requests #### Ailoot Ultra · OpenAI Responses Complete minimal JSON bodycurl · use your UTF-8 documentPython · save the complete result ```json { "model": "openai/gpt-6-luna-pro", "input": [ { "content": "Hello, how are you?", "role": "user", "type": "message" } ] } ``` ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}" export AILOOT_TEXT_FILE python3 - <<'PY_REQUEST' import json, os from pathlib import Path source_file = Path(os.environ['AILOOT_TEXT_FILE']) if not source_file.is_file(): raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document') text = source_file.read_text(encoding='utf-8') if not text.strip(): raise SystemExit('Choose a document containing text') payload = {'model': 'openai/gpt-6-luna-pro', 'input': [{'content': 'Hello, how are you?', 'role': 'user', 'type': 'message'}]} payload['input'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text Path('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8') PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \ -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path result = json.loads(Path('result.json').read_text(encoding='utf-8')) print(json.dumps(result, ensure_ascii=False, indent=2)) PY_RESULT ``` ```python import json, os from pathlib import Path source_file = Path(os.environ['AILOOT_TEXT_FILE']) if not source_file.is_file(): raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document') text = source_file.read_text(encoding='utf-8') if not text.strip(): raise SystemExit('Choose a document containing text') payload = {'model': 'openai/gpt-6-luna-pro', 'input': [{'content': 'Hello, how are you?', 'role': 'user', 'type': 'message'}]} payload['input'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text from urllib.request import Request, urlopen from urllib.error import HTTPError api_key = os.environ['AILOOT_API_KEY'] if not api_key.strip(): raise SystemExit('Set AILOOT_API_KEY before making a request') headers = {'Authorization': 'Bearer PLACEHOLDER_KEY', 'Content-Type': 'application/json'} headers['Authorization'] = 'Bearer ' + api_key request = Request('https://api.ailoot.ai/v1/responses', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST') try: with urlopen(request, timeout=120) as response: raw = response.read() Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8') except HTTPError as error: Path('result.json').write_bytes(error.read()) Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8') raise Path('result.json').write_bytes(raw) import json from pathlib import Path result = json.loads(Path('result.json').read_text(encoding='utf-8')) print(json.dumps(result, ensure_ascii=False, indent=2)) ``` ### Receive and save results #### Ailoot Ultra · OpenAI Responses json or SSE ##### Keep all completed results Keep every complete returned response, file and content part. Keep every output item and content part, actual function call\_id, encrypted reasoning and usage. In streaming retain complete event/item identity. ##### If the original response needs checking Keep request/response IDs and headers. No generic text job retrieval URL is supplied. Response fields | Field | Type | | --- | --- | | Field`id` | Typestring | | Field`status` | Typestring | | Field`output[]` | Typemessage\|reasoning\|function\_call\|other item | | Field`output[].content[]` | Typecontent part | | Field`usage` | Typeobject | Errors and next steps | Response | Condition | Next step | | --- | --- | --- | | Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. | ### Aliases #### Model aliases **Ailoot Ultra** [`openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-luna-pro&route=Ultra&caller=openai%2Fgpt-6-luna-pro&fmt=responses) #### Method path aliases Use the method paths shown above. #### Related caller IDs [`openai/gpt-6-luna-pro`](https://ailoot.ai/models/en/#m=openai%2Fgpt-6-luna-pro&route=Ultra&caller=openai%2Fgpt-6-luna-pro&fmt=responses) FAQ · OpenAI: GPT-6 Luna Pro What inputs and results are available? `POST /v1/chat/completions` · `openai/gpt-6-luna-pro`: `text` → `text` `POST /v1/messages` · `openai/gpt-6-luna-pro`: `text` → `text` `POST /v1/responses` · `openai/gpt-6-luna-pro`: `text` → `text` Which fields does the request use? `POST /v1/chat/completions` · `openai/gpt-6-luna-pro`: `model`, `messages`, `stream`, `modalities`, `provider` `POST /v1/messages` · `openai/gpt-6-luna-pro`: `model`, `messages`, `system`, `max_tokens`, `stream`, `metadata` `POST /v1/responses` · `openai/gpt-6-luna-pro`: `model`, `input`, `instructions`, `stream` What limits apply? `POST /v1/chat/completions` · `openai/gpt-6-luna-pro`: `messages.min_items`: `1` `POST /v1/messages` · `openai/gpt-6-luna-pro`: `messages.min_items`: `1`; `max_tokens.minimum`: `1` Connect Ailoot to Claude Code, OpenCode, Hermes or your own app. ## The company and its project portfolio The company and its project portfolio: millions of customers; monthly sales in the billions. ## Buy tokens at a discount. Subscription discounts for regular use. Promo codes offer up to 50% off token purchases. Subscription Choose a discounted plan for your regular requests. Promo code: up to 50% off Enter your code at checkout. The price updates to reflect the current promotion. Spending in your history The model, tokens and amount are recorded for each request. [Choose a subscription](https://ailoot.ai/docs/en/billing/subscriptions/) · [View model prices](https://ailoot.ai/models/en/) ## Connect the API to a product you sell. Use Ailoot in SaaS, apps and bots under its official service offer and licence agreement. Request a reseller licence for resale. Commercial application Add text, image, video and audio generation to paid features in your service. Reseller licence Send a description of your project and how you provide access. Request written terms for use and resale. Documents on the website The service offer, licence agreement and data processing policy are available before you connect. [Request a reseller licence](mailto:support@ailoot.ai) · [Service offer and licence agreement](https://ailoot.ai/legal/offer?lang=en) ## Ailoot · The company and its project portfolio Ailoot combines established operating experience, a large client base, stable service and ongoing KPI control. The company and its project portfolio: millions of customers; monthly sales in the billions. Ailoot brings that operating experience to API access for AI features in customer products, agents, applications and automations.