Claude Sonnet 4 is Anthropic’s model with a focus on coding and reasoning tasks. The published hosting profile accepts text, images and files and returns text. It lists reasoning and function-tool controls, with a 200,000-token context window and up to 64,000 completion tokens.
For software work, provide the relevant source, observed behavior and desired correction. Keep the failing example and actual error output when they determine the diagnosis. Ask for a focused change and the checks needed to assess its effect.
For document analysis, label the sources and name the criteria or questions to apply. A comparison can request one finding per criterion; an extraction can define the values to return and how missing information should appear. Preserve source labels so a concise answer stays connected to the material that supports it.
Identify the image, page or interface state that matters and the detail to inspect. A screenshot can support a question about visible content or behavior; a document image can add layout context to the written material. Keep the relevant source available when reviewing any extracted wording or interpretation.
The profile lists reasoning and function tools. Define the operations available to the surrounding application and retain their returned observations. A proposed action and its actual result serve different roles in the workflow; the observation supplies evidence for the next step.
When an answer will become data, state the fields and their meaning and validate the actual returned record against the source. For a human-readable result, request the conclusion and the evidence that matters to it. Reserve room for the answer within the working context and preserve completed decisions for later turns.
A useful Sonnet 4 artifact leaves the analysis or proposed change with its source references and validation, allowing the next step to continue from an inspectable result.
", "aboutText": "Claude Sonnet 4 is Anthropic’s model with a focus on coding and reasoning tasks. The published hosting profile accepts text, images and files and returns text. It lists reasoning and function-tool controls, with a 200,000-token context window and up to 64,000 completion tokens.\n\n### Code and documents with an explicit result\n\nFor software work, provide the relevant source, observed behavior and desired correction. Keep the failing example and actual error output when they determine the diagnosis. Ask for a focused change and the checks needed to assess its effect.\n\nFor document analysis, label the sources and name the criteria or questions to apply. A comparison can request one finding per criterion; an extraction can define the values to return and how missing information should appear. Preserve source labels so a concise answer stays connected to the material that supports it.\n\n### Use visual evidence purposefully\n\nIdentify the image, page or interface state that matters and the detail to inspect. A screenshot can support a question about visible content or behavior; a document image can add layout context to the written material. Keep the relevant source available when reviewing any extracted wording or interpretation.\n\n### Reasoning and application tools\n\nThe profile lists reasoning and function tools. Define the operations available to the surrounding application and retain their returned observations. A proposed action and its actual result serve different roles in the workflow; the observation supplies evidence for the next step.\n\nWhen an answer will become data, state the fields and their meaning and validate the actual returned record against the source. For a human-readable result, request the conclusion and the evidence that matters to it. Reserve room for the answer within the working context and preserve completed decisions for later turns.\n\nA useful Sonnet 4 artifact leaves the analysis or proposed change with its source references and validation, allowing the next step to continue from an inspectable result.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "a69053cdd3776e7935743b601c0b750e3b169a5387b6b6d6eb3576488f94de86", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "en", "methods": [ { "html": "claude-sonnet-4-20250514-thinkingClaude Sonnet 4 is Anthropic’s model for coding and reasoning with text, image and file input. Its published profile includes tools and reasoning controls, a 200,000-token context window and up to 64,000 completion tokens.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
Claude Sonnet 4 is Anthropic’s model with a focus on coding and reasoning tasks. The published hosting profile accepts text, images and files and returns text. It lists reasoning and function-tool controls, with a 200,000-token context window and up to 64,000 completion tokens.
For software work, provide the relevant source, observed behavior and desired correction. Keep the failing example and actual error output when they determine the diagnosis. Ask for a focused change and the checks needed to assess its effect.
For document analysis, label the sources and name the criteria or questions to apply. A comparison can request one finding per criterion; an extraction can define the values to return and how missing information should appear. Preserve source labels so a concise answer stays connected to the material that supports it.
Identify the image, page or interface state that matters and the detail to inspect. A screenshot can support a question about visible content or behavior; a document image can add layout context to the written material. Keep the relevant source available when reviewing any extracted wording or interpretation.
The profile lists reasoning and function tools. Define the operations available to the surrounding application and retain their returned observations. A proposed action and its actual result serve different roles in the workflow; the observation supplies evidence for the next step.
When an answer will become data, state the fields and their meaning and validate the actual returned record against the source. For a human-readable result, request the conclusion and the evidence that matters to it. Reserve room for the answer within the working context and preserve completed decisions for later turns.
A useful Sonnet 4 artifact leaves the analysis or proposed change with its source references and validation, allowing the next step to continue from an inspectable result.
POST /v1/chat/completionstexttext| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits claude-sonnet-4-20250514-thinking | Default— |
Fieldmessages | Typemessage[] | RequirementRequired | Values & limits Minimum items: 1 | Default— |
Fieldmessages[].role | Typestring | RequirementRequired | Values & limits Model-specific | Default— |
Fieldmessages[].content | Typestring | RequirementOptional | Values & limits Applies when: Text conversation | Default— |
Fieldstream | Typeboolean | RequirementOptional | Values & limits | Defaultfalse |
Text · UTF8 text
messages[].content
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, messages |
Parametermaterial_types | Contracttext |
Parametermessages | Contractmessage array with role/content shape |
Parameterfile_material | Contractactual UTF-8 document inserted as literal text; no file ID inferred |
Parameteroptional_controls | Contractstream |
Parametercontrol_scope | ContractText conversation; stream is a boolean and defaults to false. |
Parameteroutput_modalities | Contracttext |
Parameterhosted_operations | Contractfalse |
Parametermultimodal_input_binding | Contractnull |
Method aliases: /chat/completions
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.
Tariff references do not add request options. Supported parameters are listed for the selected method.
| Configuration | Rate schedule | Charge |
|---|---|---|
| ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens $0.006 / 1K tokens Output · Output tokens $0.03 / 1K tokens Input · Cache read $0.0006 / 1K tokens Input · Cache write $0.0075 / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model":"claude-sonnet-4-20250514-thinking","messages":[{"role":"user","content":"hello"}],"stream":false}')\n\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path("result.json").read_text())\nfor x in r.get("choices",[]):\n if x.get("message",{}).get("content"): print(x["message"]["content"])\nPY_RESULT\nfrom openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nresult=client.chat.completions.create(model="claude-sonnet-4-20250514-thinking", messages=[{"role":"user","content":"hello"}], stream=False)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n 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\n file = Path(stem + "-" + label + "." + ext)\n file.write_bytes(raw)\n print("Saved", file)\n for index, block in enumerate(data.get("content") or []):\n print("Content", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get("choices") or []:\n print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n for index, item in enumerate(data.get("output") or []):\n print("Output", index, json.dumps(item, ensure_ascii=False))\n if item.get("type") == "image_generation_call" and item.get("result"):\n save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n for ci, candidate in enumerate(data.get("candidates") or []):\n for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get("inlineData") or part.get("inline_data")\n if blob and blob.get("data"):\n mime = blob.get("mimeType") or blob.get("mime_type")\n suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(result.to_dict(mode="json"))\njson or SSE
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.
Keep request/response IDs and headers. No generic text job retrieval URL is supplied.
| Field | Type |
|---|---|
Fieldchoices[].index | Typeinteger |
Fieldchoices[].message.content | Typestring|null |
Fieldchoices[].message.tool_calls | Typetool_call[] |
Fieldchoices[].message.reasoning_content | Typestring |
Fieldchoices[].message.reasoning_details | Typeobject|array |
Fieldchoices[].finish_reason | Typestring|null |
Fieldusage | Typeobject |
| 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. |
Ailoot Ultra claude-sonnet-4-20250514-thinking
/chat/completions