Qwen-Math-Plus is the Qwen mathematical problem-solving line for equations, calculations and proofs. The maker identifies Chinese and English mathematical tasks as its focus. The input is a written problem with numbers, symbols, conditions and the quantity or statement to establish; the output is a written mathematical solution rather than an image or an executed program.
Model capabilities
The producer card lists text input and text output. This is useful for a tutoring assistant that explains a transformation, a technical assistant that works through a calculation, or a discussion of a proposed proof. The request should identify which part of the mathematics needs to be resolved: derive a general formula, evaluate a specified case, explain a disputed step, or compare two supplied approaches.
The card does not list function calling, web search, structured-output mode, response-prefix continuation, context caching, batch inference or fine-tuning as supported capabilities. In particular, the mathematical reasoning specialization should not be confused with an attached calculator or a JSON Schema interface. A worked solution is a text artifact, and any external calculation or program execution is a separate application step.
Context limits
The published specification lists a 4,096-token context window, a maximum input of 3,072 tokens and a maximum output of 3,072 tokens. This is a compact problem-solving context, not the long-document capacity of Qwen-Long or the much larger context of other Qwen editions. Keep the complete mathematical condition and the necessary working in view rather than adding an entire unrelated workbook.
Specify the required answer length according to the problem. A short algebraic calculation can return the decisive transformations and the final value; a proof can require definitions, assumptions and the main justified steps. The maximum output value is a capacity limit, not an instruction that a longer derivation is automatically better.
Preparing a mathematical question
The maker's mathematical usage guide recommends an English problem statement and LaTeX for symbols and formulas. The model card separately describes mathematical work in both English and Chinese. Preserve the exact variables, signs, indices, units and domain restrictions when preparing either language. A photograph of a problem first needs its mathematical content extracted into text; the mathematical model itself does not recognize the image.
For a general quadratic equation, state the coefficients and the condition under which the quadratic formula is being requested. Ask for the definitions, the transformation that leads to the formula, and the resulting expression. If the task concerns real solutions, ask for the cases determined by the discriminant. State whether the coefficients are symbolic or numerical and whether complex solutions belong in the answer.
The usage guide documents a boxed final expression in LaTeX. A consistent final-answer convention helps separate the result from the explanation. Request the working first and the final expression separately. The usage guide recommends leaving temperature at 0 for this mathematical workflow.
For a numerical problem, identify the units, required precision and rounding rule before asking for the calculation. For a symbolic problem, distinguish an exact expression from a decimal approximation. For a proof, state the claim and permitted assumptions so that the model has a precise target instead of an open-ended request to discuss the topic.
Editions and useful output
The maker names qwen-math-plus, the dynamically updated qwen-math-plus-latest, and snapshots such as qwen-math-plus-0919 and qwen-math-plus-0816. These names should remain distinct. A snapshot label identifies an edition; it does not add the tool-integrated training or interface features of a separately named mathematical model.
A practical tutoring request can include a learner's attempted solution and mark the first step they do not understand. Ask the model to explain that transition using the original notation, then continue to the result at the requested level of detail. Another task can present two proposed derivations and request the assumptions used by each. The value of the result comes from its connection to the supplied problem, not a generic mathematical overview.
The important boundaries are the text-only input, the compact context, and the absence of the optional tools listed above. Prepare a complete, readable mathematical statement and request a worked answer whose definitions, steps and final form correspond to that statement.
", "aboutText": "Qwen-Math-Plus is the Qwen mathematical problem-solving line for equations, calculations and proofs. The maker identifies Chinese and English mathematical tasks as its focus. The input is a written problem with numbers, symbols, conditions and the quantity or statement to establish; the output is a written mathematical solution rather than an image or an executed program.\n\nModel capabilities\n\nThe producer card lists text input and text output. This is useful for a tutoring assistant that explains a transformation, a technical assistant that works through a calculation, or a discussion of a proposed proof. The request should identify which part of the mathematics needs to be resolved: derive a general formula, evaluate a specified case, explain a disputed step, or compare two supplied approaches.\n\nThe card does not list function calling, web search, structured-output mode, response-prefix continuation, context caching, batch inference or fine-tuning as supported capabilities. In particular, the mathematical reasoning specialization should not be confused with an attached calculator or a JSON Schema interface. A worked solution is a text artifact, and any external calculation or program execution is a separate application step.\n\nContext limits\n\nThe published specification lists a 4,096-token context window, a maximum input of 3,072 tokens and a maximum output of 3,072 tokens. This is a compact problem-solving context, not the long-document capacity of Qwen-Long or the much larger context of other Qwen editions. Keep the complete mathematical condition and the necessary working in view rather than adding an entire unrelated workbook.\n\nSpecify the required answer length according to the problem. A short algebraic calculation can return the decisive transformations and the final value; a proof can require definitions, assumptions and the main justified steps. The maximum output value is a capacity limit, not an instruction that a longer derivation is automatically better.\n\nPreparing a mathematical question\n\nThe maker's mathematical usage guide recommends an English problem statement and LaTeX for symbols and formulas. The model card separately describes mathematical work in both English and Chinese. Preserve the exact variables, signs, indices, units and domain restrictions when preparing either language. A photograph of a problem first needs its mathematical content extracted into text; the mathematical model itself does not recognize the image.\n\nFor a general quadratic equation, state the coefficients and the condition under which the quadratic formula is being requested. Ask for the definitions, the transformation that leads to the formula, and the resulting expression. If the task concerns real solutions, ask for the cases determined by the discriminant. State whether the coefficients are symbolic or numerical and whether complex solutions belong in the answer.\n\nThe usage guide documents a boxed final expression in LaTeX. A consistent final-answer convention helps separate the result from the explanation. Request the working first and the final expression separately. The usage guide recommends leaving temperature at 0 for this mathematical workflow.\n\nFor a numerical problem, identify the units, required precision and rounding rule before asking for the calculation. For a symbolic problem, distinguish an exact expression from a decimal approximation. For a proof, state the claim and permitted assumptions so that the model has a precise target instead of an open-ended request to discuss the topic.\n\nEditions and useful output\n\nThe maker names qwen-math-plus, the dynamically updated qwen-math-plus-latest, and snapshots such as qwen-math-plus-0919 and qwen-math-plus-0816. These names should remain distinct. A snapshot label identifies an edition; it does not add the tool-integrated training or interface features of a separately named mathematical model.\n\nA practical tutoring request can include a learner's attempted solution and mark the first step they do not understand. Ask the model to explain that transition using the original notation, then continue to the result at the requested level of detail. Another task can present two proposed derivations and request the assumptions used by each. The value of the result comes from its connection to the supplied problem, not a generic mathematical overview.\n\nThe important boundaries are the text-only input, the compact context, and the absence of the optional tools listed above. Prepare a complete, readable mathematical statement and request a worked answer whose definitions, steps and final form correspond to that statement.", "editorialOverlay": { "copy_fields": { "practical_html": "Technical example in English
Solve a quadratic with domain cases\n\nSolve x² - 5x + 6 = 0 over the real numbers. Show a factorization, explain why the zero-product rule applies and check each solution by substitution. Then state how the answer would change if the allowed domain were real numbers strictly greater than 2. Put the final domain-specific result in a LaTeX box.A worked factorization, substitution checks and a separate boxed result for the restricted domain.The restricted-domain answer excludes any root that does not satisfy x greater than 2.qwen-math-plusQwen-Math-Plus is a text-only mathematical specialist for equations, calculations and proofs in English and Chinese. It produces worked written solutions, with a compact 4,096-token context and explicit mathematical input preparation.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
Qwen-Math-Plus is the Qwen mathematical problem-solving line for equations, calculations and proofs. The maker identifies Chinese and English mathematical tasks as its focus. The input is a written problem with numbers, symbols, conditions and the quantity or statement to establish; the output is a written mathematical solution rather than an image or an executed program.
Model capabilities
The producer card lists text input and text output. This is useful for a tutoring assistant that explains a transformation, a technical assistant that works through a calculation, or a discussion of a proposed proof. The request should identify which part of the mathematics needs to be resolved: derive a general formula, evaluate a specified case, explain a disputed step, or compare two supplied approaches.
The card does not list function calling, web search, structured-output mode, response-prefix continuation, context caching, batch inference or fine-tuning as supported capabilities. In particular, the mathematical reasoning specialization should not be confused with an attached calculator or a JSON Schema interface. A worked solution is a text artifact, and any external calculation or program execution is a separate application step.
Context limits
The published specification lists a 4,096-token context window, a maximum input of 3,072 tokens and a maximum output of 3,072 tokens. This is a compact problem-solving context, not the long-document capacity of Qwen-Long or the much larger context of other Qwen editions. Keep the complete mathematical condition and the necessary working in view rather than adding an entire unrelated workbook.
Specify the required answer length according to the problem. A short algebraic calculation can return the decisive transformations and the final value; a proof can require definitions, assumptions and the main justified steps. The maximum output value is a capacity limit, not an instruction that a longer derivation is automatically better.
Preparing a mathematical question
The maker's mathematical usage guide recommends an English problem statement and LaTeX for symbols and formulas. The model card separately describes mathematical work in both English and Chinese. Preserve the exact variables, signs, indices, units and domain restrictions when preparing either language. A photograph of a problem first needs its mathematical content extracted into text; the mathematical model itself does not recognize the image.
For a general quadratic equation, state the coefficients and the condition under which the quadratic formula is being requested. Ask for the definitions, the transformation that leads to the formula, and the resulting expression. If the task concerns real solutions, ask for the cases determined by the discriminant. State whether the coefficients are symbolic or numerical and whether complex solutions belong in the answer.
The usage guide documents a boxed final expression in LaTeX. A consistent final-answer convention helps separate the result from the explanation. Request the working first and the final expression separately. The usage guide recommends leaving temperature at 0 for this mathematical workflow.
For a numerical problem, identify the units, required precision and rounding rule before asking for the calculation. For a symbolic problem, distinguish an exact expression from a decimal approximation. For a proof, state the claim and permitted assumptions so that the model has a precise target instead of an open-ended request to discuss the topic.
Editions and useful output
The maker names qwen-math-plus, the dynamically updated qwen-math-plus-latest, and snapshots such as qwen-math-plus-0919 and qwen-math-plus-0816. These names should remain distinct. A snapshot label identifies an edition; it does not add the tool-integrated training or interface features of a separately named mathematical model.
A practical tutoring request can include a learner's attempted solution and mark the first step they do not understand. Ask the model to explain that transition using the original notation, then continue to the result at the requested level of detail. Another task can present two proposed derivations and request the assumptions used by each. The value of the result comes from its connection to the supplied problem, not a generic mathematical overview.
The important boundaries are the text-only input, the compact context, and the absence of the optional tools listed above. Prepare a complete, readable mathematical statement and request a worked answer whose definitions, steps and final form correspond to that statement.
POST /v1/chat/completionstexttext| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits qwen-math-plus | Default— |
Fieldmessages | Typemessage[] | RequirementRequired | Values & limits Minimum items: 1 | Default— |
Fieldmessages[].role | Typestring | 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— |
Fieldmessages[].content | Typestring|content_part[]|null | RequirementOptional | Values & limits | Default— |
Fieldmessages[].tool_calls | Typetool_call[] | RequirementOptional | Values & limits | Default— |
Fieldmessages[].tool_call_id | Typestring | RequirementOptional | Values & limits Applies when: role=tool; use actual returned ID | Default— |
Fieldmessages[].name | Typestring | RequirementOptional | Values & limits | Default— |
Fieldmessages[].reasoning_content | Typestring | RequirementOptional | Values & limits Applies when: Round-trip actual returned reasoning where this model uses it | Default— |
Fieldmessages[].reasoning_details | Typeobject|array | RequirementOptional | Values & limits Model-specific | Default— |
Fieldmax_tokens | Typeinteger | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— |
Fieldmax_completion_tokens | Typeinteger | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— |
Fieldstream | Typeboolean | RequirementOptional | Values & limits | Defaultfalse |
Fieldstream_options.include_usage | Typeboolean | RequirementOptional | Values & limits Model-specific | Default— |
Fieldtemperature | Typenumber | RequirementOptional | Values & limits Model-specific | Default— |
Fieldtop_p | Typenumber | RequirementOptional | Values & limits Model-specific | Default— |
Fieldstop | Typestring|string[] | RequirementOptional | Values & limits Model-specific | Default— |
Fieldtools | Typefunction_tool[] | RequirementOptional | Values & limits Model-specific | Default— |
Fieldtools[].type | Typestring | RequirementOptional | Values & limits function Model-specific | Default— |
Fieldtools[].function.name | Typestring | RequirementRequired | Values & limits Applies when: function tool supplied | Default— |
Fieldtools[].function.description | Typestring | RequirementOptional | Values & limits | Default— |
Fieldtools[].function.parameters | TypeJSON_schema | RequirementOptional | Values & limits | Default— |
Fieldtool_choice | Typestring|object | RequirementOptional | Values & limits Model-specific | Default— |
Fieldparallel_tool_calls | Typeboolean | RequirementOptional | Values & limits Model-specific | Default— |
Fieldresponse_format | Typeobject | RequirementOptional | Values & limits Model-specific | Default— |
Fieldreasoning_effort | Typestring | RequirementOptional | Values & limits Model-specific | Default— |
Fieldreasoning | Typeobject | RequirementOptional | Values & limits Model-specific | Default— |
Fieldservice_tier | Typestring | RequirementOptional | Values & limits Model-specific | Default— |
Fieldinstructions | Typestring | RequirementOptional | Values & limits Compatibility field | Default— |
Fieldfunctions | Typefunction[] | RequirementOptional | Values & limits Model-specific | Default— |
Fieldfunction_call | Typestring|object | RequirementOptional | Values & limits Model-specific | Default— |
Fieldprompt_cache_options | Typeobject | RequirementOptional | Values & limits Model-specific | Default— |
Fieldmodalities | Typestring[] | RequirementOptional | Values & limits text | Default— |
Fieldprovider | Typeobject | RequirementOptional | Values & limits Conditions: provider.options is rejected on this Ultra text route | Default— |
Fieldcache_control.ttl | Typestring | RequirementOptional | Values & limits Conditions: 1h is rejected in actual prompt-cache locations | Default— |
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, temperature, top_p, stop, max_tokens, max_completion_tokens, reasoning, response_format, tools, tool_choice |
Parametercontrol_scope | Contractmodel-specific; user function tools differ from hosted tools |
Parameteroutput_modalities | Contracttext |
Parameterhosted_operations | Contractfalse |
Parametermultimodal_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.
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 $0.001144 / 1K tokens Output · Output tokens $0.00344 / 1K tokens Input · Cache read $0 / 1K tokens Input · Cache write $0 / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "qwen-math-plus", "messages": [{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}]}')\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='qwen-math-plus',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}])\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"))\nfrom openai import OpenAI\nimport os\nfrom pathlib import Path\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)\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\nwith client.chat.completions.stream(model='qwen-math-plus',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n for event in stream:\n payload=event.to_dict(mode="json")\n log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode="json"),"stream-result")\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 qwen-math-plus
Use the method paths shown above.
qwen-math-plusQwen-Math-Plus is a text-only mathematical specialist for equations, calculations and proofs in English and Chinese. It produces worked written solutions, with a compact 4,096-token context and explicit mathematical input preparation.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
Qwen-Math-Plus is the Qwen mathematical problem-solving line for equations, calculations and proofs. The maker identifies Chinese and English mathematical tasks as its focus. The input is a written problem with numbers, symbols, conditions and the quantity or statement to establish; the output is a written mathematical solution rather than an image or an executed program.
Model capabilities
The producer card lists text input and text output. This is useful for a tutoring assistant that explains a transformation, a technical assistant that works through a calculation, or a discussion of a proposed proof. The request should identify which part of the mathematics needs to be resolved: derive a general formula, evaluate a specified case, explain a disputed step, or compare two supplied approaches.
The card does not list function calling, web search, structured-output mode, response-prefix continuation, context caching, batch inference or fine-tuning as supported capabilities. In particular, the mathematical reasoning specialization should not be confused with an attached calculator or a JSON Schema interface. A worked solution is a text artifact, and any external calculation or program execution is a separate application step.
Context limits
The published specification lists a 4,096-token context window, a maximum input of 3,072 tokens and a maximum output of 3,072 tokens. This is a compact problem-solving context, not the long-document capacity of Qwen-Long or the much larger context of other Qwen editions. Keep the complete mathematical condition and the necessary working in view rather than adding an entire unrelated workbook.
Specify the required answer length according to the problem. A short algebraic calculation can return the decisive transformations and the final value; a proof can require definitions, assumptions and the main justified steps. The maximum output value is a capacity limit, not an instruction that a longer derivation is automatically better.
Preparing a mathematical question
The maker's mathematical usage guide recommends an English problem statement and LaTeX for symbols and formulas. The model card separately describes mathematical work in both English and Chinese. Preserve the exact variables, signs, indices, units and domain restrictions when preparing either language. A photograph of a problem first needs its mathematical content extracted into text; the mathematical model itself does not recognize the image.
For a general quadratic equation, state the coefficients and the condition under which the quadratic formula is being requested. Ask for the definitions, the transformation that leads to the formula, and the resulting expression. If the task concerns real solutions, ask for the cases determined by the discriminant. State whether the coefficients are symbolic or numerical and whether complex solutions belong in the answer.
The usage guide documents a boxed final expression in LaTeX. A consistent final-answer convention helps separate the result from the explanation. Request the working first and the final expression separately. The usage guide recommends leaving temperature at 0 for this mathematical workflow.
For a numerical problem, identify the units, required precision and rounding rule before asking for the calculation. For a symbolic problem, distinguish an exact expression from a decimal approximation. For a proof, state the claim and permitted assumptions so that the model has a precise target instead of an open-ended request to discuss the topic.
Editions and useful output
The maker names qwen-math-plus, the dynamically updated qwen-math-plus-latest, and snapshots such as qwen-math-plus-0919 and qwen-math-plus-0816. These names should remain distinct. A snapshot label identifies an edition; it does not add the tool-integrated training or interface features of a separately named mathematical model.
A practical tutoring request can include a learner's attempted solution and mark the first step they do not understand. Ask the model to explain that transition using the original notation, then continue to the result at the requested level of detail. Another task can present two proposed derivations and request the assumptions used by each. The value of the result comes from its connection to the supplied problem, not a generic mathematical overview.
The important boundaries are the text-only input, the compact context, and the absence of the optional tools listed above. Prepare a complete, readable mathematical statement and request a worked answer whose definitions, steps and final form correspond to that statement.
POST /v1/messagestextjson, sse| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits qwen-math-plus | Default— |
Fieldmessages | Typemessage[] | RequirementRequired | Values & limits | Default— |
Fieldmessages[].role | Typestring | RequirementRequired | Values & limits user, assistant | Default— |
Fieldmessages[].content | Typestring | RequirementRequired | Values & limits | Default— |
Fieldmax_tokens | Typeinteger | RequirementRequired | Values & limits | Default— |
Fieldstream | Typeboolean | RequirementOptional | Values & limits | Defaultfalse |
Text · UTF-8 text
messages[].content string
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, messages, max_tokens |
Parameteroptional_controls | Contractstream |
Parametermaterial_types | Contracttext |
Parametertext_file_material | ContractRead the actual UTF-8 document and put its text in the indicated input or message content string. |
Lifecycle: synchronous_or_streamed
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 $0.001144 / 1K tokens Output · Output tokens $0.00344 / 1K tokens Input · Cache read $0 / 1K tokens Input · Cache write $0 / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
{\n "model": "qwen-math-plus",\n "max_tokens": 128,\n "messages": [\n {\n "role": "user",\n "content": "Summarize the incident report."\n }\n ],\n "stream": false\n}set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'qwen-math-plus', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -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\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'qwen-math-plus', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n with urlopen(request, timeout=120) as response:\n raw = response.read()\n Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n Path('result.json').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nJSON or SSE
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.
Keep request/response IDs and headers. No generic text job retrieval URL is supplied.
| Field | Type |
|---|---|
Fieldid | Typestring |
Fieldmodel | Typestring |
Fieldcontent[] | Typetext|thinking|tool_use|other content block |
Fieldstop_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 qwen-math-plus
Use the method paths shown above.
Technical example in English
Solve a quadratic with domain cases\n\nSolve x² - 5x + 6 = 0 over the real numbers. Show a factorization, explain why the zero-product rule applies and check each solution by substitution. Then state how the answer would change if the allowed domain were real numbers strictly greater than 2. Put the final domain-specific result in a LaTeX box.A worked factorization, substitution checks and a separate boxed result for the restricted domain.The restricted-domain answer excludes any root that does not satisfy x greater than 2.