Model Comparison
Qwen2.5-VL-32B-Instruct
vs
Qwen2.5-VL-7B-Instruct
Feb 28, 2026
Pricing
Input
$
0.27
/ M Tokens
$
0.05
/ M Tokens
Output
$
0.27
/ M Tokens
$
0.05
/ M Tokens
Metadata
Create on
Mar 21, 2025
Jan 26, 2025
License
APACHE-2.0
APACHE-2.0
Provider
Qwen
Qwen
Specification
State
Available
Available
Architecture
Vision Transformer (ViT) with window attention, SwiGLU, RMSNorm, and mRoPE, aligned with Qwen2.5 LLM structure
Vision-Language Model (VLM) combining a Vision Transformer (ViT) with window attention, SwiGLU, and RMSNorm, aligned with the Qwen2.5 LLM structure. It utilizes mRoPE for temporal understanding and YaRN for long text context handling.
Calibrated
Yes
No
Mixture of Experts
No
No
Total Parameters
32B
7B
Activated Parameters
32B
7B
Reasoning
No
No
Precision
FP8
FP8
Context length
131K
33K
Max Tokens
131K
4K
Supported Functionality
Serverless
Supported
Supported
Serverless LoRA
Not supported
Not supported
Fine-tuning
Not supported
Not supported
Embeddings
Not supported
Not supported
Rerankers
Not supported
Not supported
Support image input
Not supported
Not supported
JSON Mode
Not supported
Not supported
Structured Outputs
Not supported
Not supported
Tools
Not supported
Not supported
Fim Completion
Not supported
Not supported
Chat Prefix Completion
Supported
Supported
Qwen2.5-VL-32B-Instruct in Comparison
See how Qwen2.5-VL-32B-Instruct compares with other popular models across key dimensions.
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