Produck Inference · Model
Qwen3 Next 80B API
A text chat route where generated output length deserves cost attention.
Input / 1M$0.10
Output / 1M$1.10
Context262K
Produck model ID
qwen3-next-80bIntegration
API examples
Send a server-side HTTP request to the OpenAI-compatible chat completions endpoint. The examples use the public Produck model ID.
Shell
curl https://api.produckai.com/v1/chat/completions \
-H "Authorization: Bearer $PRODUCK_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model":"qwen3-next-80b",
"messages":[
{"role":"user","content":"Hello"}
]
}'Python · requests
import os
import requests
url = "https://api.produckai.com/v1/chat/completions"
headers = {
"Authorization": f"Bearer {os.environ['PRODUCK_API_KEY']}",
"Content-Type": "application/json",
}
payload = {"model": "qwen3-next-80b", "messages": [{"role": "user", "content": "Hello"}]}
response = requests.post(url, headers=headers, json=payload, timeout=60)
response.raise_for_status()
print(response.json())TypeScript · server-side fetch
// Server-side TypeScript (Node.js)
const response = await fetch("https://api.produckai.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.PRODUCK_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "qwen3-next-80b",
messages: [{ role: "user", content: "Hello" }],
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Workload choice
Why use Qwen3 Next 80B?
Qwen3 Next 80B has a stated context display through Produck Inference. Its output price is higher than its input price, so estimate response length carefully when comparing it with other listed routes.
Current API surface
Supported through Produck Inference
- Text chat
- Streaming
Model facts
- Public model ID
qwen3-next-80b- Public context display
- 262K
- API endpoint
https://api.produckai.com/v1/chat/completions
Workload guidance
Match the route to the request.
Good fit for
- Text chat workloads that need its stated context window
- Teams that model input and output spend separately
- Evaluation across the published model routes
Consider another model when
- Long generated responses make output price your main constraint
- A smaller window is enough and lower token prices matter more
Alternatives
Related models
Inference Engineering