Qwen3 VL 235B A22B Thinking
VerifiedOpen-weight multimodal model for advanced text and image reasoning.
About Qwen3 VL 235B A22B Thinking
The model uses a large-scale multimodal transformer design that jointly processes visual and textual data. It incorporates 235 billion total parameters while remaining fully open-weight for broad accessibility. A context length of 131072 tokens enables handling of lengthy documents paired with images.
Strengths include native support for combined text-image inputs and the flexibility of open weights for customization. The architecture is suited to tasks that require integration of visual understanding with language reasoning at scale.
Typical usage covers visual question answering, document interpretation, and multimodal analysis in research or production environments. Developers fine-tune or deploy it directly for applications needing robust cross-modal comprehension.
Capabilities
How Qwen3 VL 235B A22B Thinking compares
Qwen3 VL 235B A22B Thinking (striped bar) vs other multimodal on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Qwen3 VL 235B A22B Thinking ranks #49 of 102
Nova 2 LiteSources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Visual Question Answering on Complex Scenes
The model performs detailed image interpretation combined with text reasoning to answer questions about visual content accurately.
Long-Context Document Analysis with Visuals
It processes documents up to 131072 tokens while integrating images, charts, and diagrams for comprehensive understanding.
Step-by-Step Reasoning on Code and Diagrams
Users can leverage its chain-of-thought capabilities to interpret technical diagrams and code structures in multimodal inputs.
Strengths & limitations
Strengths
- +Strong fusion of visual and textual information
- +Effective handling of extended contexts
- +Robust reasoning on complex multimodal inputs
Limitations
- –High inference compute requirements
- –Limited to static images
- –May hallucinate details in ambiguous visuals
Cost calculator
Estimate what Qwen3 VL 235B A22B Thinking would cost for your usage.
Based on Qwen3 VL 235B A22B Thinking's $0.26/1M input · $2.60/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "qwen/qwen3-vl-235b-a22b-thinking",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: qwen/qwen3-vl-235b-a22b-thinking
Editor's verdict
Qwen3 VL 235B A22B Thinking is Alibaba Qwen's open-weight multimodal with a 131K-token context window.
At $2.60 per 1M output tokens, it is mid-priced for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to strong fusion of visual and textual information and effective handling of extended contexts.
Frequently asked questions
The model supports a context window of 131072 tokens for handling extended inputs.
User reviews
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Other Qwen models
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