DeepSeek VL2 Tiny vs GLM-4.7 Comparison
Comparing DeepSeek VL2 Tiny and GLM-4.7 across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek VL2 Tiny and GLM-4.7 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
GLM-4.7 has 355.0B more parameters than DeepSeek VL2 Tiny, making it 11833.3% larger.
Context Window
Maximum input and output token capacity
Only GLM-4.7 specifies input context (202,800 tokens). Only GLM-4.7 specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
Both DeepSeek VL2 Tiny and GLM-4.7 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek VL2 Tiny
GLM-4.7
License
Usage and distribution terms
DeepSeek VL2 Tiny is licensed under deepseek, while GLM-4.7 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek VL2 Tiny was released on 2024-12-13, while GLM-4.7 was released on 2025-12-22.
GLM-4.7 is 12 months newer than DeepSeek VL2 Tiny.
Dec 13, 2024
1.3 years ago
Dec 22, 2025
2 months ago
1.0yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
DeepSeek VL2 Tiny
View detailsDeepSeek
GLM-4.7
View detailsZhipu AI
Detailed Comparison
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