DeepSeek R1 Distill Qwen 1.5B vs GLM-4.7 Comparison
Comparing DeepSeek R1 Distill Qwen 1.5B and GLM-4.7 across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while GLM-4.7 is better at 1 benchmark (GPQA).
GLM-4.7 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
GLM-4.7 has 356.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 20012.4% 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
GLM-4.7 supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.
GLM-4.7 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 1.5B
GLM-4.7
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while GLM-4.7 was released on 2025-12-22.
GLM-4.7 is 11 months newer than DeepSeek R1 Distill Qwen 1.5B.
Jan 20, 2025
1.1 years ago
Dec 22, 2025
2 months ago
11mo 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
GLM-4.7
View detailsZhipu AI
Detailed Comparison
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