Source: https://ailoot.ai/models/en/qwen-qwen3-30b-a3b-thinking-2507/
Canonical: https://ailoot.ai/models/en/qwen-qwen3-30b-a3b-thinking-2507/
Language: en

# Qwen3 30B A3B Thinking 2507

[Markdown](https://ailoot.ai/models/en/qwen-qwen3-30b-a3b-thinking-2507/index.md) · [JSON](https://ailoot.ai/models/en/qwen-qwen3-30b-a3b-thinking-2507/facts.json)

## [Qwen3 30B A3B Thinking 2507](https://ailoot.ai/models/en/qwen-qwen3-30b-a3b-thinking-2507/)

Qwen3-30B-A3B-Thinking-2507 is Qwen’s thinking-only text model for demanding mathematics, science, coding and logical reasoning. This fixed 2507 edition provides a native 262,144-token context and a longer reasoning budget, with documented tool-calling and conditional ultra-long-context workflows.

- [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/qwen-qwen3-30b-a3b-thinking-2507/#method-0)
- [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/qwen-qwen3-30b-a3b-thinking-2507/#method-1)
- [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/qwen-qwen3-30b-a3b-thinking-2507/#method-2)
- [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/qwen-qwen3-30b-a3b-thinking-2507/#method-3)

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

Highlights: the fixed Thinking-2507 release

Qwen3-30B-A3B-Thinking-2507 is a text-generation model focused on difficult reasoning. Qwen describes improvements in logic, mathematics, science, coding, instruction following, tool use and text generation, together with longer thinking sequences and stronger long-context understanding. Select this exact 2507 edition when the task benefits from sustained reasoning, such as examining competing explanations, solving a multi-stage mathematical problem or working through a complex code change.

Model overview and mode

The mixture-of-experts model has 30.5 billion total parameters and 3.3 billion activated parameters, with 128 experts and eight selected per token across 48 layers. Its native context is 262,144 tokens. It accepts text and returns text; tool results are provided through a connected application workflow. This checkpoint supports thinking only. It is distinct from the earlier hybrid Qwen3-30B-A3B, its FP8 edition and Qwen3-30B-A3B-Instruct-2507. The hybrid model’s non-thinking switch should not be assumed to apply here.

The default chat template already starts the reasoning sequence with an opening thinking marker, so an explicit enable\_thinking=True setting is unnecessary. A returned sequence may contain the closing marker without repeating the opening marker. The maker’s example separates the reasoning from the final answer. Preserve that distinction when requesting a concrete deliverable: a proof conclusion, a patch or a decision table should remain easy to find after the longer explanation.

Preparing a difficult task

Give the model the complete problem statement, constraints and relevant evidence. For a code change, include the existing function, a failing input and expected behavior, then request a proposed patch with an explanation of edge cases. For a scientific question, separate observations from assumptions and ask which conclusion follows from each. For a long policy or specification, retain section identifiers and request a concise decision backed by the relevant clauses. These are practical uses of the documented reasoning domains, not claims that the model has executed a patch or validated an experiment.

Because this version can reason at length, reserve space for both reasoning and the final artifact. Qwen advises retaining a context above 131,072 tokens where possible when configuring the model, even if a smaller context would ease memory pressure. The native context figure includes the sequence budget; it is not a promise that all of it can be used for a document while leaving unlimited answer space.

Agentic use

The maker documents tool calling and recommends Qwen-Agent for tool templates and parsing, including integration with configured tools and code-interpreter workflows. Define the tools and the intended result explicitly. For example, an application could let the model inspect retrieved evidence, use a permitted calculator, then produce a report explaining the calculation. Retrieval and execution belong to the connected tools; the model’s tool-calling capability does not itself establish access to the internet, a code environment or business systems.

Processing ultra-long text

Qwen documents an optional workflow reaching approximately one million tokens by combining Dual Chunk Attention with MInference sparse attention. The first technique divides long sequences into chunks while preserving interactions across them; the second focuses computation on selected attention relationships. This is an additional configuration path, beyond the native 262,144-token context. The maker’s recipe requires its special long-context configuration and estimates roughly 240 GB of total GPU memory for weights, cached attention state and peak activations.

That recipe has concrete resource limits: cached sequence state, activation memory and total input length can each exhaust the configured capacity. A million-token workflow therefore depends on configuration, memory and supported attention implementation. For practical document review, start with the relevant material, mark document boundaries and request traceable evidence instead of treating the largest possible input as a substitute for a clear question.

Generation guidance and limits

Qwen recommends temperature 0.6, top\_p 0.95, top\_k 20 and min\_p 0. It suggests a 32,768-token output budget for most queries and 81,920 for unusually difficult mathematical or programming problems. These are generation-budget recommendations rather than a separately published hard output ceiling. A presence penalty between zero and two can reduce repetition, but higher values may mix languages or slightly lower quality.

Specify the final-answer format in the prompt, such as a delimited mathematical result or an answer field for a multiple-choice question. Keep only the final-answer portion in conversation history, as the maker recommends. Longer reasoning is useful when it produces a checkable result; inspect assumptions, calculations and proposed code before relying on the outcome.

Practical task

### Solve a constrained staffing assignment

Technical example in English

```
Solve a constrained staffing assignment

Assign three reviewers, Ada, Ben and Cy, to morning, afternoon and evening shifts, one each. Ada cannot work evening. Ben must work later than Ada. Cy cannot work morning. List every valid assignment and explain how each constraint eliminates alternatives. Finish with whether the assignment is unique; do not assume additional availability.
```

#### Expected result

```
An enumeration of all valid assignments, a constraint check and a separate uniqueness conclusion.
```

#### Check the result

```
Every assignment uses all three shifts once and satisfies Ben later than Ada without adding availability rules.
```

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `Qwen/Qwen3-30B-A3B-Thinking-2507`

[`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=chat)

Alibaba /`Qwen/Qwen3-30B-A3B-Thinking-2507`

Model ID

- `Qwen/Qwen3-30B-A3B-Thinking-2507`
- `qwen3-30b-a3b-thinking-2507`

### Overview

Qwen3-30B-A3B-Thinking-2507 is Qwen’s thinking-only text model for demanding mathematics, science, coding and logical reasoning. This fixed 2507 edition provides a native 262,144-token context and a longer reasoning budget, with documented tool-calling and conditional ultra-long-context workflows.

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 Qwen/Qwen3-30B-A3B-Thinking-2507 | Default— |
| Field`messages` | Type`message[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— |
| Field`messages[].role` | Type`string` | RequirementRequired | Values & limits Model-specific | Default— |
| Field`messages[].content` | Type`string` | RequirementOptional | Values & limits Applies when: Text conversation | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse |

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 |
| Parameter`control_scope` | ContractText conversation; stream is a boolean and defaults to false. |
| Parameter`output_modalities` | Contracttext |
| Parameter`hosted_operations` | Contractfalse |
| Parameter`multimodal_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.

### 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 **$0.0002** / 1K tokens Output · Output tokens **$0.0008** / 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 SDK

```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":"Qwen/Qwen3-30B-A3B-Thinking-2507","messages":[{"role":"user","content":"hello"}],"stream":false}')

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="Qwen/Qwen3-30B-A3B-Thinking-2507", messages=[{"role":"user","content":"hello"}], stream=False)
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"))
```

### 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** [`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=chat), [`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=chat)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=chat), [`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=chat)

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `Qwen/Qwen3-30B-A3B-Thinking-2507`

[`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=messages)

Alibaba /`Qwen/Qwen3-30B-A3B-Thinking-2507`

Model ID

- `Qwen/Qwen3-30B-A3B-Thinking-2507`
- `qwen3-30b-a3b-thinking-2507`

### Overview

Qwen3-30B-A3B-Thinking-2507 is Qwen’s thinking-only text model for demanding mathematics, science, coding and logical reasoning. This fixed 2507 edition provides a native 262,144-token context and a longer reasoning budget, with documented tool-calling and conditional ultra-long-context workflows.

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 Qwen/Qwen3-30B-A3B-Thinking-2507 | 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 **$0.0002** / 1K tokens Output · Output tokens **$0.0008** / 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": "Qwen/Qwen3-30B-A3B-Thinking-2507",
  "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': 'Qwen/Qwen3-30B-A3B-Thinking-2507', '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': 'Qwen/Qwen3-30B-A3B-Thinking-2507', '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** [`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=messages), [`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=messages)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=messages), [`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=messages)

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `qwen3-30b-a3b-thinking-2507`

[`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=chat)

Alibaba /`qwen3-30b-a3b-thinking-2507`

Model ID

- `Qwen/Qwen3-30B-A3B-Thinking-2507`
- `qwen3-30b-a3b-thinking-2507`

### Overview

Qwen3-30B-A3B-Thinking-2507 is Qwen’s thinking-only text model for demanding mathematics, science, coding and logical reasoning. This fixed 2507 edition provides a native 262,144-token context and a longer reasoning budget, with documented tool-calling and conditional ultra-long-context workflows.

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 qwen3-30b-a3b-thinking-2507 | 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 **$0.0002** / 1K tokens Output · Output tokens **$0.0008** / 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": "qwen3-30b-a3b-thinking-2507", "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='qwen3-30b-a3b-thinking-2507',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='qwen3-30b-a3b-thinking-2507',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** [`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=chat), [`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=chat)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=chat), [`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=chat)

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `qwen3-30b-a3b-thinking-2507`

[`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=messages)

Alibaba /`qwen3-30b-a3b-thinking-2507`

Model ID

- `Qwen/Qwen3-30B-A3B-Thinking-2507`
- `qwen3-30b-a3b-thinking-2507`

### Overview

Qwen3-30B-A3B-Thinking-2507 is Qwen’s thinking-only text model for demanding mathematics, science, coding and logical reasoning. This fixed 2507 edition provides a native 262,144-token context and a longer reasoning budget, with documented tool-calling and conditional ultra-long-context workflows.

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 qwen3-30b-a3b-thinking-2507 | 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 **$0.0002** / 1K tokens Output · Output tokens **$0.0008** / 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": "qwen3-30b-a3b-thinking-2507",
  "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': 'qwen3-30b-a3b-thinking-2507', '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': 'qwen3-30b-a3b-thinking-2507', '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** [`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=messages), [`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=messages)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`Qwen/Qwen3-30B-A3B-Thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=Qwen%2FQwen3-30B-A3B-Thinking-2507&fmt=messages), [`qwen3-30b-a3b-thinking-2507`](https://ailoot.ai/models/en/#m=Qwen%2FQwen3-30B-A3B-Thinking-2507&route=Ultra&caller=qwen3-30b-a3b-thinking-2507&fmt=messages)

FAQ · Qwen/Qwen3-30B-A3B-Thinking-2507

What inputs and results are available?

`POST /v1/chat/completions` · `Qwen/Qwen3-30B-A3B-Thinking-2507`: `text` → `text` `POST /v1/messages` · `Qwen/Qwen3-30B-A3B-Thinking-2507`: `text` → `json`, `sse` `POST /v1/chat/completions` · `qwen3-30b-a3b-thinking-2507`: `text` → `text` `POST /v1/messages` · `qwen3-30b-a3b-thinking-2507`: `text` → `json`, `sse`

Which fields does the request use?

`POST /v1/chat/completions` · `Qwen/Qwen3-30B-A3B-Thinking-2507`: `model`, `messages`, `stream` `POST /v1/messages` · `Qwen/Qwen3-30B-A3B-Thinking-2507`: `model`, `messages`, `max_tokens`, `stream` `POST /v1/chat/completions` · `qwen3-30b-a3b-thinking-2507`: `model`, `messages`, `stream`, `modalities`, `provider` `POST /v1/messages` · `qwen3-30b-a3b-thinking-2507`: `model`, `messages`, `max_tokens`, `stream`

What limits apply?

`POST /v1/chat/completions` · `Qwen/Qwen3-30B-A3B-Thinking-2507`: `messages.min_items`: `1` `POST /v1/chat/completions` · `qwen3-30b-a3b-thinking-2507`: `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.

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Reseller licence

Send a description of your project and how you provide access. Request written terms for use and resale.

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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.