Model Comparison

DeepSeek R1 Zero vs Nemotron 3 Nano (30B A3B)

Nemotron 3 Nano (30B A3B) significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek R1 Zero outperforms in 0 benchmarks, while Nemotron 3 Nano (30B A3B) is better at 1 benchmark (GPQA).

Nemotron 3 Nano (30B A3B) significantly outperforms across most benchmarks.

Fri Apr 17 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
Fri Apr 17 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Zero
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
NVIDIA
Nemotron 3 Nano (30B A3B)
Input tokens$0.06
Output tokens$0.24
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

639.0B diff

DeepSeek R1 Zero has 639.0B more parameters than Nemotron 3 Nano (30B A3B), making it 1996.9% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
NVIDIA
Nemotron 3 Nano (30B A3B)
32.0Bparameters
671.0B
DeepSeek R1 Zero
32.0B
Nemotron 3 Nano (30B A3B)

Context Window

Maximum input and output token capacity

Only Nemotron 3 Nano (30B A3B) specifies input context (262,144 tokens). Only Nemotron 3 Nano (30B A3B) specifies output context (262,144 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
NVIDIA
Nemotron 3 Nano (30B A3B)
Input262,144 tokens
Output262,144 tokens
Fri Apr 17 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Nemotron 3 Nano (30B A3B) uses NVIDIA Open Model License Agreement .

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek R1 Zero

MIT

Open weights

Nemotron 3 Nano (30B A3B)

NVIDIA Open Model License Agreement

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Nemotron 3 Nano (30B A3B) was released on 2025-12-15.

Nemotron 3 Nano (30B A3B) is 11 months newer than DeepSeek R1 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.2 years ago

Nemotron 3 Nano (30B A3B)

Dec 15, 2025

4 months ago

10mo newer

Knowledge Cutoff

When training data ends

Nemotron 3 Nano (30B A3B) has a documented knowledge cutoff of 2025-11-28, while DeepSeek R1 Zero's cutoff date is not specified.

We can confirm Nemotron 3 Nano (30B A3B)'s training data extends to 2025-11-28, but cannot make a direct comparison without DeepSeek R1 Zero's cutoff date.

DeepSeek R1 Zero

—

Nemotron 3 Nano (30B A3B)

Nov 2025

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
NVIDIA
Larger context window (262,144 tokens)
Higher GPQA score (75.0% vs 73.3%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Zero
NVIDIA
Nemotron 3 Nano (30B A3B)

FAQ

Common questions about DeepSeek R1 Zero vs Nemotron 3 Nano (30B A3B)

Nemotron 3 Nano (30B A3B) significantly outperforms across most benchmarks. DeepSeek R1 Zero is made by DeepSeek and Nemotron 3 Nano (30B A3B) 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%. Nemotron 3 Nano (30B A3B) scores AIME 2025: 99.2%, WMT24++: 86.2%, MMLU-Pro: 78.3%, GPQA: 75.0%, LiveCodeBench v6: 68.3%.
DeepSeek R1 Zero supports an unknown number of tokens and Nemotron 3 Nano (30B A3B) supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs NVIDIA Open Model License Agreement ). See the full comparison above for benchmark-by-benchmark results.
DeepSeek R1 Zero is developed by DeepSeek and Nemotron 3 Nano (30B A3B) is developed by NVIDIA.