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Model details

Qwen3-VL-Plus

Qwen3-VL-Plus is a vision-language model built for complex multimodal reasoning tasks, serving as the flagship variant in Alibaba's Qwen3-VL family. The model processes both visual and textual inputs to handle document parsing, chart analysis, OCR, image reasoning, and GUI automation across desktop and mobile interfaces. Its native vision-language architecture enables spatial reasoning and deep chain-of-thought processing for intricate visual tasks, with a large context window that accommodates lengthy documents and multi-image conversations. The architecture balances strong multimodal understanding with computational efficiency, making it suitable for developers seeking advanced vision capabilities without self-hosted infrastructure.

The model supports 33 languages with built-in deep thinking and function calling for agentic workflows, enabling structured outputs in JSON and other formats alongside context caching for repeated interactions. As the highest-performing model in the Qwen3-VL series, it delivers improved accuracy on complex vision tasks through chain-of-thought reasoning that breaks down visual problems step by step. It also supports video analysis with extended context handling for temporal reasoning. These capabilities position it well for research, document-heavy workflows, and applications requiring precise visual understanding across diverse inputs.

iFlowqwen3-vl-plusqwen

Quick Info

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Provider
iFlow
Model key
qwen3-vl-plus
Release date
Jan 1, 2025
Last updated
Jan 1, 2025
Knowledge cutoff
2024-12
Input modalities
Output modalities
Capabilities

Cost

A provider subscription or plan supersedes token-based pricing for this model.

Limits

Output tokens
32,000 tokens
Context window
256,000 tokens

Latest news about Qwen3-VL-Plus

iFlow

CoverageBenchmark

A third-party benchmark published on 2026-06-22 by Crazyrouter compares qwen3-vl-plus against gemini-2.5-flash using an OpenAI-compatible image_url workflow (chat/completions with mixed text and image content) tested on June 21, 2026. Across six runs on the Python and GitHub logos, qwen3-vl-plus scored 6/6 correct visu The benchmark reports explicit pricing through the Crazyrouter proxy: qwen3-vl-plus at $0.1429 input and $1.4286 output per 1M tokens, versus gemini-2.5-flash at $0.17 input and $0.68 output, yielding an estimated $0.3848 versus $0.6168 per 10k test-style calls. Both models returned zero/missing image_token fields, so

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