Source: https://ailoot.ai/models/en/qwen3-5-omni-flash-2026-03-15/ Canonical: https://ailoot.ai/models/en/qwen3-5-omni-flash-2026-03-15/ Language: en # qwen3.5-omni-flash-2026-03-15 [Markdown](https://ailoot.ai/models/en/qwen3-5-omni-flash-2026-03-15/index.md) · [JSON](https://ailoot.ai/models/en/qwen3-5-omni-flash-2026-03-15/facts.json) ## [qwen3.5-omni-flash-2026-03-15](https://ailoot.ai/models/en/qwen3-5-omni-flash-2026-03-15/) Qwen3.5-Omni-Flash 2026-03-15 is a multimodal snapshot that accepts text, images, audio and video and returns text or speech. Use its separate edition for repeatable media briefs and spoken explanations, with documented input and output boundaries. - [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `qwen3.5-omni-flash-2026-03-15`](https://ailoot.ai/models/en/qwen3-5-omni-flash-2026-03-15/#method-0) - [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `qwen3.5-omni-flash-2026-03-15`](https://ailoot.ai/models/en/qwen3-5-omni-flash-2026-03-15/#method-1) About the model This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below. Qwen3.5-Omni-Flash 2026-03-15 is Alibaba’s named March 15 multimodal snapshot for text creation, voice assistants and multimedia analysis. It accepts text, images, audio and video, including mixed input, and produces text or text with speech. Its dated identity is distinct from the undated Flash alias and from realtime models. A recorded task can keep this edition name together with the media and instructions being reviewed. Its input can join a picture with a spoken question, or combine a video’s visuals and sound with written instructions. This makes it useful when a text-only summary would lose the connection between what is seen and what is heard. For a media brief, ask separately for the visible sequence, on-screen wording and spoken content, and request source-relative timestamps when the order of events matters. Sound effects and other non-speech audio can contribute to the analysis alongside speech. For a voice response, specify the answer’s language, audience and delivery. Qwen’s guide documents instructions for volume, speaking rate and emotion. It lists 113 audio-input languages and dialects and 36 speech-output languages and dialects, including English, French, German and Russian. The voice catalogue identifies Tina as the default and includes options such as Serena and Ethan. Choose the voice and ask for a concise explanation at a measured pace rather than relying on the input voice to determine the output style. The documented HTTP speech workflow returns streaming text and Base64-encoded audio chunks. Its WAV example uses 24 kHz, mono, 16-bit PCM; an application can collect the chunks into an audio file or decode them for playback as they arrive. This is streamed generation from a submitted request. Live turn detection, interruption handling and microphone conversation belong to separately named realtime models. Qwen3.5-Omni’s family table does not offer a deep-thinking mode. This Flash snapshot lists web search and Function Calling, with Function Calling limited to Beijing Chat Completions and text output. Structured Outputs is marked unsupported: a request for chronological sections is a text-format instruction rather than a constrained JSON mode. Tool execution belongs to the surrounding application, which returns the tool result for the next model step. Prefix completion, context caching, batch inference and fine-tuning are also marked unsupported for this snapshot. The published context window is 262,144 tokens, with maximum input of 196,608 tokens and maximum output of 65,536 tokens. Mixed media and text share the context budget. Alibaba’s HTTP guide allows up to three hours of audio or one hour of video for this series; it lists AMR, WAV, 3GP, 3GPP, AAC and MP3 audio and MP4, AVI, MKV, MOV, FLV and WMV video. URL-based audio or video files may be up to 2 GB, while Base64-encoded media must be smaller than 10 MB. These are the manufacturer’s file-workflow limits, distinct from the model introduction’s description of understanding over ten hours of audio or over 400 seconds of 720p video sampled at 1 FPS. Images have their own preparation limits in that guide: up to 20 MB per URL-based image, dimensions greater than 10 pixels on each side and an aspect ratio no more extreme than 200:1. The guide allows up to 2,048 URL-based images or audio files and 512 URL-based video files; Base64 input allows up to 250 files. These transfer limits remain subject to the shared input-token budget. The series can combine several media types in one request. Choose the relevant excerpt, make small labels readable and explain how separate inputs relate. The documented file-count ceilings vary by modality and transfer method, while every input must still fit the shared token budget. Custom voice cloning is not supported by the named March 15 snapshot in the Qwen3.5-Omni guide. Choose a documented catalogue voice for spoken output and describe the desired delivery in the written brief. Do not transfer the undated Flash alias’s separate voice-enrolment workflow into this edition. A catalogue voice identifies the speaker style, while instructions can shape volume, speaking rate and emotion. For a repeatable media report, supply the relevant clip and ask for the events, visible wording and speech in distinct chronological sections, each tied to source timestamps. For an educational response, add a diagram and a learner’s recorded question: “Explain the labelled parts, answer the audio question in English and provide text plus calm speech.” Keep the input excerpt, edition name and prompt together, and specify whether the output should transcribe the source or explain it for a new audience. Practical task ### Separate speech from scene notes Technical example in English ``` Separate speech from scene notes Prepare a chronological report from these transcribed media notes: 00:00 a green indicator is visible; 00:03 speaker says “Wait for the light”; 00:05 indicator turns amber; 00:08 speaker says “Now disconnect.” Separate described visuals from quoted speech and list the action instruction with its time. Return text only. ``` #### Expected result ``` A timeline with distinct visual and speech entries, followed by the timed instruction. ``` #### Check the result ``` Check that the instruction stays at 00:08 and that the indicator change is not described as something the speaker said. ``` **Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `qwen3.5-omni-flash-2026-03-15` [`qwen3.5-omni-flash-2026-03-15`](https://ailoot.ai/models/en/#m=qwen3.5-omni-flash-2026-03-15&route=Ultra&caller=qwen3.5-omni-flash-2026-03-15&fmt=chat) Alibaba /`qwen3.5-omni-flash-2026-03-15` ### Overview Qwen3.5-Omni-Flash 2026-03-15 is a multimodal snapshot that accepts text, images, audio and video and returns text or speech. Use its separate edition for repeatable media briefs and spoken explanations, with documented input and output boundaries. 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 qwen3.5-omni-flash-2026-03-15 | 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 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 #### Ailoot rates #### Prices by configuration | Configuration | Rate schedule | Charge | | --- | --- | --- | | ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens **$0.00069** / 1K tokens Output · Output tokens **$0.00418** / 1K tokens Input · Cache read **$0** / 1K tokens Input · Cache write **$0** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/) ### Example requests #### Ailoot Ultra · OpenAI Chat curlPython SDKPython stream ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "qwen3.5-omni-flash-2026-03-15", "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='qwen3.5-omni-flash-2026-03-15',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='qwen3.5-omni-flash-2026-03-15',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** [`qwen3.5-omni-flash-2026-03-15`](https://ailoot.ai/models/en/#m=qwen3.5-omni-flash-2026-03-15&route=Ultra&caller=qwen3.5-omni-flash-2026-03-15&fmt=chat) #### Method path aliases Use the method paths shown above. #### Related caller IDs [`qwen3.5-omni-flash-2026-03-15`](https://ailoot.ai/models/en/#m=qwen3.5-omni-flash-2026-03-15&route=Ultra&caller=qwen3.5-omni-flash-2026-03-15&fmt=chat) **Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `qwen3.5-omni-flash-2026-03-15` [`qwen3.5-omni-flash-2026-03-15`](https://ailoot.ai/models/en/#m=qwen3.5-omni-flash-2026-03-15&route=Ultra&caller=qwen3.5-omni-flash-2026-03-15&fmt=messages) Alibaba /`qwen3.5-omni-flash-2026-03-15` ### Overview Qwen3.5-Omni-Flash 2026-03-15 is a multimodal snapshot that accepts text, images, audio and video and returns text or speech. Use its separate edition for repeatable media briefs and spoken explanations, with documented input and output boundaries. Accepted inputs Text Results json · sse ### Available in Ailoot · inputs & methods **Ailoot Ultra · Anthropic Messages** `POST /v1/messages` Input types `text` Output types `json`, `sse` Output format JSON or SSE | Field | Type | Requirement | Values & limits | Default | | --- | --- | --- | --- | --- | | Field`model` | Type`string` | RequirementRequired | Values & limits qwen3.5-omni-flash-2026-03-15 | Default— | | Field`messages` | Type`message[]` | RequirementRequired | Values & limits | Default— | | Field`messages[].role` | Type`string` | RequirementRequired | Values & limits user, assistant | Default— | | Field`messages[].content` | Type`string` | RequirementRequired | Values & limits | Default— | | Field`max_tokens` | Type`integer` | RequirementRequired | Values & limits | Default— | | Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse | Input material combinations **Text** · UTF-8 text `messages[].content string` Method parameters and lifecycle | Parameter | Contract | | --- | --- | | Parameter`content_type` | Contractapplication/json | | Parameter`required` | Contractmodel, messages, max\_tokens | | Parameter`optional_controls` | Contractstream | | Parameter`material_types` | Contracttext | | Parameter`text_file_material` | ContractRead the actual UTF-8 document and put its text in the indicated input or message content string. | Lifecycle: `synchronous_or_streamed` ### 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 #### Ailoot rates #### Prices by configuration | Configuration | Rate schedule | Charge | | --- | --- | --- | | ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens **$0.00069** / 1K tokens Output · Output tokens **$0.00418** / 1K tokens Input · Cache read **$0** / 1K tokens Input · Cache write **$0** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens | Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/) ### Example requests #### Ailoot Ultra · Anthropic Messages Complete minimal JSON bodycurl · use your UTF-8 documentPython · save the complete result ```json { "model": "qwen3.5-omni-flash-2026-03-15", "max_tokens": 128, "messages": [ { "role": "user", "content": "Summarize the incident report." } ], "stream": false } ``` ```bash set -eu : "${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': 'qwen3.5-omni-flash-2026-03-15', 'max_tokens': 128, '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': 'qwen3.5-omni-flash-2026-03-15', 'max_tokens': 128, '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** [`qwen3.5-omni-flash-2026-03-15`](https://ailoot.ai/models/en/#m=qwen3.5-omni-flash-2026-03-15&route=Ultra&caller=qwen3.5-omni-flash-2026-03-15&fmt=messages) #### Method path aliases Use the method paths shown above. #### Related caller IDs [`qwen3.5-omni-flash-2026-03-15`](https://ailoot.ai/models/en/#m=qwen3.5-omni-flash-2026-03-15&route=Ultra&caller=qwen3.5-omni-flash-2026-03-15&fmt=messages) FAQ · qwen3.5-omni-flash-2026-03-15 What inputs and results are available? `POST /v1/chat/completions` · `qwen3.5-omni-flash-2026-03-15`: `text` → `text` `POST /v1/messages` · `qwen3.5-omni-flash-2026-03-15`: `text` → `json`, `sse` Which fields does the request use? `POST /v1/chat/completions` · `qwen3.5-omni-flash-2026-03-15`: `model`, `messages`, `stream`, `modalities`, `provider` `POST /v1/messages` · `qwen3.5-omni-flash-2026-03-15`: `model`, `messages`, `max_tokens`, `stream` What limits apply? `POST /v1/chat/completions` · `qwen3.5-omni-flash-2026-03-15`: `messages.min_items`: `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.