Model Comparison

DeepSeek-R1 vs Llama-3.3 Nemotron Super 49B v1

Comparing DeepSeek-R1 and Llama-3.3 Nemotron Super 49B v1 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Llama-3.3 Nemotron Super 49B v1 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.

Lowest available price from all providers
Fri Apr 03 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

621.1B diff

DeepSeek-R1 has 621.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 1244.7% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
671.0B
DeepSeek-R1
49.9B
Llama-3.3 Nemotron Super 49B v1

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).

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input- tokens
Output- tokens
Fri Apr 03 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 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.

DeepSeek-R1

MIT

Open weights

Llama-3.3 Nemotron Super 49B v1

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18.

Llama-3.3 Nemotron Super 49B v1 is 2 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.0 years ago

1mo newer

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'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's cutoff date.

DeepSeek-R1

—

Llama-3.3 Nemotron Super 49B v1

Dec 2023

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
NVIDIA

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
NVIDIA
Llama-3.3 Nemotron Super 49B v1

FAQ

Common questions about DeepSeek-R1 vs Llama-3.3 Nemotron Super 49B v1

DeepSeek-R1 (DeepSeek) and Llama-3.3 Nemotron Super 49B v1 (NVIDIA) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Llama-3.3 Nemotron Super 49B v1 scores MATH-500: 96.6%, MT-Bench: 91.7%, MBPP: 91.3%, Arena Hard: 88.3%, BFCL v2: 73.7%.
DeepSeek-R1 supports 131K tokens and Llama-3.3 Nemotron Super 49B v1 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1 is developed by DeepSeek and Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA.