Qwen2.5-VL-32B-Instruct
About Qwen2.5-VL-32B-Instruct
Qwen2.5-VL-32B-Instruct is a multimodal large language model released by the Qwen team, part of the Qwen2.5-VL series. This model is not only proficient in recognizing common objects but is highly capable of analyzing texts, charts, icons, graphics, and layouts within images. It acts as a visual agent that can reason and dynamically direct tools, capable of computer and phone use. Additionally, the model can accurately localize objects in images, and generate structured outputs for data like invoices and tables. Compared to its predecessor Qwen2-VL, this version has enhanced mathematical and problem-solving abilities through reinforcement learning, with response styles adjusted to better align with human preferences
Available Serverless
Run queries immediately, pay only for usage
$
0.27
/
$
0.27
Per 1M Tokens (input/output)
Metadata
Specification
State
Available
Architecture
Vision Transformer (ViT) with window attention, SwiGLU, RMSNorm, and mRoPE, aligned with Qwen2.5 LLM structure
Calibrated
Yes
Mixture of Experts
No
Total Parameters
32B
Activated Parameters
32B
Reasoning
No
Precision
FP8
Context length
131K
Max Tokens
131K
Supported Functionality
Serverless
Supported
Serverless LoRA
Not supported
Fine-tuning
Not supported
Embeddings
Not supported
Rerankers
Not supported
Support image input
Supported
JSON Mode
Not supported
Structured Outputs
Not supported
Tools
Not supported
Fim Completion
Not supported
Chat Prefix Completion
Supported
Compare with Other Models
See how this model stacks up against others.
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Total Context:
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Max output:
262K
Input:
$
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/ M Tokens
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Input:
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Max output:
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Input:
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Total Context:
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Max output:
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Input:
$
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Total Context:
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Max output:
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Input:
$
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Max output:
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