Qwen3.6 35B A3B

Qwen · Text · Context 262.1K · max output 65.5K tokens

qwen3.6-35b-a3b Try

Prompt caching
14% below list price

Pricing

Per 1 million tokens
	MarkasAI	Vendor list price
Input	Rp 5.733	Rp 6.709
Output	Rp 34.395	Rp 40.253
Cache	Rp 5.733
Cache write	Rp 5.733

MarkasAI sale prices in Rupiah, read from the same catalog as GET /v1/models. Prices can change and apply to later requests.

Specifications

Model ID: qwen3.6-35b-a3b
Provider: Qwen
Type: Text
Endpoint: POST /v1/chat/completions
Context window: 262,144 tokens
Output limit per request: 65,536 tokens

About this model

Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...

Quoted from the provider's public catalog, in English.

Call example

curl https://api.markas.ai.id/v1/chat/completions \
  -H "Authorization: Bearer $MARKASAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.6-35b-a3b",
    "messages": [{"role": "user", "content": "What is an API?"}],
    "max_tokens": 300
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://api.markas.ai.id/v1", api_key=os.environ["MARKASAI_API_KEY"])

resp = client.chat.completions.create(
    model="qwen3.6-35b-a3b",
    messages=[{"role": "user", "content": "What is an API?"}],
    max_tokens=300,
)
print(resp.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.markas.ai.id/v1", apiKey: process.env.MARKASAI_API_KEY });

const resp = await client.chat.completions.create({
  model: "qwen3.6-35b-a3b",
  messages: [{ role: "user", content: "What is an API?" }],
  max_tokens: 300,
});
console.log(resp.choices[0].message.content);

Keep your API key in the MARKASAI_API_KEY environment variable. Read the endpoint docs

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