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Alibaba (Qwen) / qwen3-vl-235b-a22b-instruct

Qwen3 VL 235B Instruct

Qwen3 VL 235B Instruct is a multimodal model from Alibaba (Qwen), suited for Complex visual analysis.

Image understandingChat & customer supportAutomation & agents

Context

128K

tokens

Input

$0.480

/ 1M tokens

Output

$1.92

/ 1M tokens

Quality

#72

Elo 1158

Overview

What this model is good for

Qwen3 VL 235B Instruct is a multimodal model from Alibaba (Qwen), suited for Complex visual analysis.

Model capabilities

Multimodal

Supports mixed text-image input and can use 128K tokens of context for longer material.

Tool calling

Can call tools or functions, so product flows can connect model output to backend actions.

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$0.480/ 1M tokens
Output$1.92/ 1M tokens

Light production run

100K input + 25K output

$0.096

Higher-volume run

1M input + 250K output

$0.960

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-235b-a22b-instruct

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-235b-a22b-instruct",
"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-235b-a22b-instruct",
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-235b-a22b-instruct",
messages: [{ role: "user", content: "Hello." }],
});
console.log(resp.choices[0].message.content);