deCloud
MA CHAIN · 20260131
← All models

Qwen: Qwen3 Next 80B A3B Instruct

qwen/qwen3-next-80b-a3b-instruct

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...

Context
262K
Input MA / 1M
0.054
Output MA / 1M
0.66

Billing follows the provider's own reported cost rather than the catalogue price — cached input is cheaper, and reasoning tokens bill as output. Your usage page is the record of what you actually paid.

Capabilities

ChatCodeToolsStructured

Try it

One free message per account, no deposit needed. The reply is length-capped — it's a taste, not a quota.

Connect a wallet and sign in to use your free try.

Connect a wallet

Call it

Every model goes through the same endpoint — just use this page's ID as model.

curl https://macdecloud.com/v1/chat/completions \
  -H "Authorization: Bearer dcld-sk-..." \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen/qwen3-next-80b-a3b-instruct","messages":[{"role":"user","content":"Hello"}]}'

Streaming

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-next-80b-a3b-instruct","stream":true,"messages":[{"role":"user","content":"hi"}]}'

Function calling

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-next-80b-a3b-instruct",
  "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"]
      }
    }
  }]
}

Structured output

Supports response_format, so the model returns JSON matching a schema you give it instead of prose you have to parse.

{
  "model": "qwen/qwen3-next-80b-a3b-instruct",
  "messages": [{ "role": "user", "content": "..." }],
  "response_format": {
    "type": "json_schema",
    "json_schema": {
      "name": "result",
      "schema": {
        "type": "object",
        "properties": { "answer": { "type": "string" } },
        "required": ["answer"]
      }
    }
  }
}
Use it from Claude Code / Cursor / opencode →