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Qwentext+image->text

Qwen: Qwen3 VL 235B A22B Instruct

Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table extraction, multilingual OCR). The series emphasizes robust perception (recognition of diverse real-world and synthetic categories), spatial understanding (2D/3D grounding), and long-form visual comprehension, with competitive results on public multimodal benchmarks for both perception and reasoning. Beyond analysis, Qwen3-VL supports agentic interaction and tool use: it can follow complex instructions over multi-image, multi-turn dialogues; align text to video timelines for precise temporal queries; and operate GUI elements for automation tasks. The models also enable visual coding workflows—turning sketches or mockups into code and assisting with UI debugging—while maintaining strong text-only performance comparable to the flagship Qwen3 language models. This makes Qwen3-VL suitable for production scenarios spanning document AI, multilingual OCR, software/UI assistance, spatial/embodied tasks, and research on vision-language agents.

Context Window

262K

Input Price

$0.2000/M tokens

Output Price

$1.20/M tokens

Modality

text+image->text

Pricing Breakdown
Cost per million tokens for input and output
Input$0.2000/M tokens
Output$1.20/M tokens

Cost Example: Processing 10,000 input tokens and generating 1,000 output tokens would cost approximately $0.003200

Context Window Size
Maximum tokens the model can process in a single request
Context Window262K tokens
26% of 1M max

~197K

Words Equivalent

~131

Pages of Text

~2621

Code Functions

Best Use Cases
What this model excels at
CodingProgrammingDevelopmentMathReasoningAnalysisVisionImage-analysisMultimodalData-analysisAnalyticsResearchAcademic

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