Model Comparison
DeepSeek-R1 vs Llama 3.1 Nemotron Ultra 253B v1
Comparing DeepSeek-R1 and Llama 3.1 Nemotron Ultra 253B v1 across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1 and Llama 3.1 Nemotron Ultra 253B v1 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 418.0B more parameters than Llama 3.1 Nemotron Ultra 253B v1, making it 165.2% 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).
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while Llama 3.1 Nemotron Ultra 253B v1 uses Llama 3.1 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 3.1 Community License
Open weights
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while Llama 3.1 Nemotron Ultra 253B v1 was released on 2025-04-07.
Llama 3.1 Nemotron Ultra 253B v1 is 3 months newer than DeepSeek-R1.
Jan 20, 2025
1.3 years ago
Apr 7, 2025
1.1 years ago
2mo newerKnowledge Cutoff
When training data ends
Llama 3.1 Nemotron Ultra 253B v1 has a documented knowledge cutoff of 2023-12-01, while DeepSeek-R1's cutoff date is not specified.
We can confirm Llama 3.1 Nemotron Ultra 253B v1's training data extends to 2023-12-01, but cannot make a direct comparison without DeepSeek-R1's cutoff date.
—
Dec 2023
Outputs Comparison
Key Takeaways
DeepSeek-R1
View detailsDeepSeek
No standout differentiators in the data we have for this pair.
Detailed Comparison
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FAQ
Common questions about DeepSeek-R1 vs Llama 3.1 Nemotron Ultra 253B v1.