Model Comparison
DeepSeek-R1 vs Granite 3.3 8B Base
Comparing DeepSeek-R1 and Granite 3.3 8B Base across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1 and Granite 3.3 8B Base 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
DeepSeek-R1 has 662.8B more parameters than Granite 3.3 8B Base, making it 8113.0% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-R1 specifies input context (131,072 tokens). Only DeepSeek-R1 specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
Granite 3.3 8B Base supports multimodal inputs, whereas DeepSeek-R1 does not.
Granite 3.3 8B Base can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1
Granite 3.3 8B Base
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while Granite 3.3 8B Base uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while Granite 3.3 8B Base was released on 2025-04-16.
Granite 3.3 8B Base is 3 months newer than DeepSeek-R1.
Jan 20, 2025
1.3 years ago
Apr 16, 2025
1.1 years ago
2mo newerKnowledge Cutoff
When training data ends
Granite 3.3 8B Base has a documented knowledge cutoff of 2024-04-01, while DeepSeek-R1's cutoff date is not specified.
We can confirm Granite 3.3 8B Base's training data extends to 2024-04-01, but cannot make a direct comparison without DeepSeek-R1's cutoff date.
—
Apr 2024
Outputs Comparison
Key Takeaways
DeepSeek-R1
View detailsDeepSeek
Detailed Comparison
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FAQ
Common questions about DeepSeek-R1 vs Granite 3.3 8B Base.