qwen/qwen3-235b-a22b-2507Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...
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curl https://macdecloud.com/v1/chat/completions \
-H "Authorization: Bearer dcld-sk-..." \
-H "Content-Type: application/json" \
-d '{"model":"qwen/qwen3-235b-a22b-2507","messages":[{"role":"user","content":"Hello"}]}'Add "stream": true for token-by-token output over standard SSE.
curl -N https://macdecloud.com/v1/chat/completions \
-H "Authorization: Bearer dcld-sk-..." \
-H "Content-Type: application/json" \
-d '{"model":"qwen/qwen3-235b-a22b-2507","stream":true,"messages":[{"role":"user","content":"hi"}]}'This model supports tools. Replies may carry tool_calls; run them and append the results as role: "tool" messages, then call again.
{
"model": "qwen/qwen3-235b-a22b-2507",
"messages": [{ "role": "user", "content": "What's the weather in Paris?" }],
"tools": [{
"type": "function",
"function": {
"name": "get_weather",
"parameters": {
"type": "object",
"properties": { "city": { "type": "string" } },
"required": ["city"]
}
}
}]
}Supports response_format, so the model returns JSON matching a schema you give it instead of prose you have to parse.
{
"model": "qwen/qwen3-235b-a22b-2507",
"messages": [{ "role": "user", "content": "..." }],
"response_format": {
"type": "json_schema",
"json_schema": {
"name": "result",
"schema": {
"type": "object",
"properties": { "answer": { "type": "string" } },
"required": ["answer"]
}
}
}
}