Qwen: Qwen2.5 VL 32B Instruct
Qwen 2.5 VL 32B Instruct is a vision-language model at a competitive price, but without benchmark data it cannot be reliably assessed — it may suit multimodal tasks but businesses should evaluate it carefully before production deployment.
Assessment date: March 12, 2026
Our methodology takes into account a range of factors including pricing, functionality, capabilities, benchmark performance, and real-world applicability. Rankings are reviewed and updated regularly as new models are released. Issues with our rankings? Contact us
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.
Capabilities
Architecture
| Modality | Text + Image → Text |
| Tokenizer | Qwen |
| Parameters | 32B |
Model Information
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.20 | $0.000200 |
| Output | $0.60 | $0.000600 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
