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Qwen: Qwen2.5 VL 32B Instruct

qwen/qwen2.5-vl-32b-instruct

Model weights

Qwen2.5-VL-32B is a multimodal vision-language model fine-tuned through reinforcement learning for enhanced mathematical reasoning, structured outputs, and visual problem-solving capabilities. It excels at visual analysis tasks, including object recognition, textual interpretation within images, and precise event localization in extended videos. Qwen2.5-VL-32B demonstrates state-of-the-art performance across multimodal benchmarks such as MMMU, MathVista, and VideoMME, while maintaining strong reasoning and clarity in text-based tasks like MMLU, mathematical problem-solving, and code generation.

Modalities

Context

33K

Released

Mar 24, 2025

Knowledge Cutoff

Jun 2024

ActivityFAQ

Activity

Token volume and request traffic to this model over time.

About Qwen: Qwen2.5 VL 32B Instruct

OpenRouter makes Qwen: Qwen2.5 VL 32B Instruct available through a unified, OpenAI-compatible API using the model ID qwen/qwen2.5-vl-32b-instruct.

Qwen: Qwen2.5 VL 32B Instruct accepts text and images and returns text. It has a 32,768-token context window.

It was released on March 24, 2025; its knowledge cutoff is June 30, 2024.

More models from Qwen

  • Qwen3.8 27B
  • Qwen3 Reranker 8B
  • Qwen3 ASR 1.7B

Frequently asked questions

Qwen2.5-VL-32B is a multimodal vision-language model fine-tuned through reinforcement learning for enhanced mathematical reasoning, structured outputs, and visual problem-solving capabilities. It excels at visual analysis tasks, including object recognition, textual interpretation within images, and precise event localization in extended videos.

Qwen2.5 VL 32B Instruct has a 32,768 token context window.

Qwen2.5 VL 32B Instruct accepts text and images as input and returns text.

Qwen3.8 27B, Qwen3.8 2.4T A95B, Qwen3.8 Max and 47 more are other text models from Qwen.

Qwen2.5 VL 32B Instruct was released on March 24, 2025. Its knowledge cutoff is June 30, 2024.