Model Comparison
DeepSeek-R1-0528 vs Llama-3.3 Nemotron Super 49B v1
DeepSeek-R1-0528 significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1-0528 outperforms in 2 benchmarks (AIME 2025, GPQA), while Llama-3.3 Nemotron Super 49B v1 is better at 0 benchmarks.
DeepSeek-R1-0528 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 621.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 1244.7% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-R1-0528 specifies input context (131,072 tokens). Only DeepSeek-R1-0528 specifies output context (131,072 tokens).
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while Llama-3.3 Nemotron Super 49B 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-R1-0528 was released on 2025-05-28, while Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18.
DeepSeek-R1-0528 is 2 months newer than Llama-3.3 Nemotron Super 49B v1.
May 28, 2025
11 months ago
2mo newerMar 18, 2025
1.2 years ago
Knowledge Cutoff
When training data ends
Llama-3.3 Nemotron Super 49B v1 has a documented knowledge cutoff of 2023-12-31, while DeepSeek-R1-0528's cutoff date is not specified.
We can confirm Llama-3.3 Nemotron Super 49B v1's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek-R1-0528's cutoff date.
—
Dec 2023
Outputs Comparison
Key Takeaways
DeepSeek-R1-0528
View detailsDeepSeek
No standout differentiators in the data we have for this pair.
Detailed Comparison
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FAQ
Common questions about DeepSeek-R1-0528 vs Llama-3.3 Nemotron Super 49B v1.