Model Comparison

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

Both models are evenly matched across the benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek R1 Zero outperforms in 1 benchmarks (GPQA), while Llama-3.3 Nemotron Super 49B v1 is better at 1 benchmark (MATH-500).

Both models are evenly matched across the benchmarks.

Wed Apr 08 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 08 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Zero
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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 Zero has 621.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 1244.7% larger.

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

License

Usage and distribution terms

DeepSeek R1 Zero 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 Zero

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 Zero 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 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.2 years ago

Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.1 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 Zero'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 Zero's cutoff date.

DeepSeek R1 Zero

—

Llama-3.3 Nemotron Super 49B v1

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Higher GPQA score (73.3% vs 66.7%)
NVIDIA
Higher MATH-500 score (96.6% vs 95.9%)

Detailed Comparison

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

FAQ

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

Both models are evenly matched across the benchmarks. DeepSeek R1 Zero is made by DeepSeek and Llama-3.3 Nemotron Super 49B v1 is made by NVIDIA. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. 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%.
Key differences include licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek R1 Zero is developed by DeepSeek and Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA.