Alibaba (Qwen) / qwen3-vl-32b-thinking

Qwen3 Vl 32b Thinking

Qwen3 Vl 32b Thinking is a general text model from Alibaba (Qwen), suited for General chat; API-compatible workloads.

Chat & customer support

Context

32K

tokens

Input

$0.192

/ 1M tokens

Output

$0.768

/ 1M tokens

Quality

#170

Elo 1005

Overview

What this model is good for

Qwen3 Vl 32b Thinking is a general text model from Alibaba (Qwen), suited for General chat; API-compatible workloads.

Model capabilities

Streaming

Supports streamed responses for chat, assistants, and interfaces that need visible incremental output.

Model maker

Model maker and access

This section shows the model maker, SeaLink model ID, protocol, and pricing information.

Alibaba (Qwen)

Called through SeaLink's unified account, balance, and OpenAI-compatible API.

Protocol

OpenAI-compatible Chat Completions

Base URL: https://test.sealink.io/v1

Pricing

Pricing and cost sense

Prices come from the current model catalog. Simple estimates help users judge whether the model fits production volume.

Input$0.192/ 1M tokens

Output$0.768/ 1M tokens

Light production run

100K input + 25K output

$0.038

Higher-volume run

1M input + 250K output

$0.384

Actual billing follows usage logs and billing records; caching and media pricing depend on the endpoint.

API

Copy into your code

The model page should make it clear which model to copy, which base URL to use, and where to get an API Key.

model

qwen3-vl-32b-thinking

base_url

https://test.sealink.io/v1

Auth

Bearer $SEALINK_API_KEY

cURL

curl https://test.sealink.io/v1/chat/completions \
  -H "Authorization: Bearer $SEALINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3-vl-32b-thinking",
    "messages": [{"role": "user", "content": "Hello."}]
  }'

Python (OpenAI SDK)

from openai import OpenAI
client = OpenAI(base_url="https://test.sealink.io/v1", api_key="<your-sealink-key>")

resp = client.chat.completions.create(
    model="qwen3-vl-32b-thinking",
    messages=[{"role": "user", "content": "Hello."}],
)
print(resp.choices[0].message.content)

Node.js (OpenAI SDK)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://test.sealink.io/v1",
  apiKey: process.env.SEALINK_API_KEY,
});

const resp = await client.chat.completions.create({
  model: "qwen3-vl-32b-thinking",
  messages: [{ role: "user", content: "Hello." }],
});
console.log(resp.choices[0].message.content);