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
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