qwen3.5-122b-a10b· Released Feb 25, 2026
qwen/qwen3.5-122b-a10b
The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of...
Input
From$0.276/M
Output
From$2.244/M
Context
Up to 131K
Max output
Up to 33K
Modalities
TextImageVideoTextInput and output show the lowest price across upstreams, for reference. Your actual prices are listed per upstream below.
Upstreams & pricing
| Upstream | Context | Max output | Input $/1M | Output $/1M | Data policy |
|---|---|---|---|---|---|
MorgenrotAI/Globalfp8From price | 131K | 33K | $0.276 | $2.244 | — |
Routed in real time — you pay the listed price of whichever upstream serves your call. Data policies reflect each upstream's own data terms and its agreement with us. We do not independently audit upstream implementations.
How to call
bashrequest.sh
curl https://api.lune.io/v1/chat/completions \
-H "Authorization: Bearer $API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen/qwen3.5-122b-a10b",
"messages": [
{"role": "user", "content": "Say hello in five words."}
]
}'pythonrequest.py
from openai import OpenAI
import os
client = OpenAI(
api_key=os.environ["API_KEY"],
base_url="https://api.lune.io/v1",
)
resp = client.chat.completions.create(
model="qwen/qwen3.5-122b-a10b",
messages=[{"role": "user", "content": "Say hello in five words."}],
)
print(resp.choices[0].message.content)tsrequest.ts
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.API_KEY,
baseURL: "https://api.lune.io/v1",
});
const resp = await client.chat.completions.create({
model: "qwen/qwen3.5-122b-a10b",
messages: [{ role: "user", content: "Say hello in five words." }],
});
console.log(resp.choices[0].message.content);gomain.go
package main
import (
"context"
"fmt"
"os"
"github.com/sashabaranov/go-openai"
)
func main() {
cfg := openai.DefaultConfig(os.Getenv("API_KEY"))
cfg.BaseURL = "https://api.lune.io/v1"
client := openai.NewClientWithConfig(cfg)
resp, err := client.CreateChatCompletion(
context.Background(),
openai.ChatCompletionRequest{
Model: "qwen/qwen3.5-122b-a10b",
Messages: []openai.ChatCompletionMessage{
{Role: "user", Content: "Say hello in five words."},
},
},
)
if err != nil {
panic(err)
}
fmt.Println(resp.Choices[0].Message.Content)
}