Qwen: Qwen2.5 VL 32B Instruct
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.
Description
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.
ArchitectureАрхитектура
- Modality:
- text+image->text
- InputModalities:
- text, image
- OutputModalities:
- text
- Tokenizer:
- Qwen
ContextAndLimits
- ContextLength:
- 16384 Tokens
- MaxResponseTokens:
- 16384 Tokens
- Moderation:
- Disabled
PricingRUB
- Request:
- ₽
- Image:
- ₽
- WebSearch:
- ₽
- InternalReasoning:
- ₽
- Prompt1KTokens:
- ₽
- Completion1KTokens:
- ₽
DefaultParameters
- Temperature:
- 0
UserComments