Qwen3 32B

Qwen · Text · Context 32K · max output 8.2K tokens

qwen3-32b Try

Prompt caching
14% below list price

Pricing

Per 1 million tokens
	MarkasAI	Vendor list price
Input	Rp 2.447	Rp 2.863
Output	Rp 9.784	Rp 11.450
Cache	Rp 2.447
Cache write	Rp 2.447

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: qwen3-32b
Provider: Qwen
Type: Text
Endpoint: POST /v1/chat/completions
Context window: 32,000 tokens
Output limit per request: 8,192 tokens

About this model

Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...

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": "qwen3-32b",
    "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="qwen3-32b",
    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: "qwen3-32b",
  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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