Model Comparison
GLM-5 vs Qwen2-VL-72B-Instruct
Comparing GLM-5 and Qwen2-VL-72B-Instruct across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5 and Qwen2-VL-72B-Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
GLM-5 has 670.6B more parameters than Qwen2-VL-72B-Instruct, making it 913.6% larger.
Context Window
Maximum input and output token capacity
Only GLM-5 specifies input context (200,000 tokens). Only GLM-5 specifies output context (128,000 tokens).
Input Capabilities
Supported data types and modalities
Qwen2-VL-72B-Instruct supports multimodal inputs, whereas GLM-5 does not.
Qwen2-VL-72B-Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5
Qwen2-VL-72B-Instruct
License
Usage and distribution terms
GLM-5 is licensed under MIT, while Qwen2-VL-72B-Instruct uses tongyi-qianwen.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
tongyi-qianwen
Open weights
Release Timeline
When each model was launched
GLM-5 was released on 2026-02-11, while Qwen2-VL-72B-Instruct was released on 2024-08-29.
GLM-5 is 18 months newer than Qwen2-VL-72B-Instruct.
Feb 11, 2026
2 months ago
1.5yr newerAug 29, 2024
1.7 years ago
Knowledge Cutoff
When training data ends
Qwen2-VL-72B-Instruct has a documented knowledge cutoff of 2023-06-30, while GLM-5's cutoff date is not specified.
We can confirm Qwen2-VL-72B-Instruct's training data extends to 2023-06-30, but cannot make a direct comparison without GLM-5's cutoff date.
—
Jun 2023
Outputs Comparison
Key Takeaways
GLM-5
View detailsZhipu AI
Qwen2-VL-72B-Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about GLM-5 vs Qwen2-VL-72B-Instruct.