Model Comparison

DeepSeek-V3 0324 vs Nemotron Nano 9B v2

Nemotron Nano 9B v2 shows notably better performance in the majority of benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3 0324 outperforms in 1 benchmarks (GPQA), while Nemotron Nano 9B v2 is better at 2 benchmarks (LiveCodeBench, MATH-500).

Nemotron Nano 9B v2 shows notably better performance in the majority of benchmarks.

Mon Apr 13 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
Mon Apr 13 2026 • llm-stats.com
DeepSeek
DeepSeek-V3 0324
Input tokens$0.28
Output tokens$1.14
Best providerNovita
NVIDIA
Nemotron Nano 9B v2
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

662.1B diff

DeepSeek-V3 0324 has 662.1B more parameters than Nemotron Nano 9B v2, making it 7439.3% larger.

DeepSeek
DeepSeek-V3 0324
671.0Bparameters
NVIDIA
Nemotron Nano 9B v2
8.9Bparameters
671.0B
DeepSeek-V3 0324
8.9B
Nemotron Nano 9B v2

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
NVIDIA
Nemotron Nano 9B v2
Input- tokens
Output- tokens
Mon Apr 13 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while Nemotron Nano 9B v2 uses NVIDIA Open Model License Agreement .

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

DeepSeek-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Nemotron Nano 9B v2

NVIDIA Open Model License Agreement

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 0324 was released on 2025-03-25, while Nemotron Nano 9B v2 was released on 2025-08-18.

Nemotron Nano 9B v2 is 5 months newer than DeepSeek-V3 0324.

DeepSeek-V3 0324

Mar 25, 2025

1.1 years ago

Nemotron Nano 9B v2

Aug 18, 2025

7 months ago

4mo newer

Knowledge Cutoff

When training data ends

Nemotron Nano 9B v2 has a documented knowledge cutoff of 2024-09-01, while DeepSeek-V3 0324's cutoff date is not specified.

We can confirm Nemotron Nano 9B v2's training data extends to 2024-09-01, but cannot make a direct comparison without DeepSeek-V3 0324's cutoff date.

DeepSeek-V3 0324

—

Nemotron Nano 9B v2

Sep 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Higher GPQA score (68.4% vs 64.0%)
NVIDIA
Higher LiveCodeBench score (71.1% vs 49.2%)
Higher MATH-500 score (97.8% vs 94.0%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3 0324
NVIDIA
Nemotron Nano 9B v2

FAQ

Common questions about DeepSeek-V3 0324 vs Nemotron Nano 9B v2

Nemotron Nano 9B v2 shows notably better performance in the majority of benchmarks. DeepSeek-V3 0324 is made by DeepSeek and Nemotron Nano 9B v2 is made by NVIDIA. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%. Nemotron Nano 9B v2 scores MATH-500: 97.8%, IFEval: 90.3%, AIME 2025: 72.1%, LiveCodeBench: 71.1%, BFCL_v3_MultiTurn: 66.9%.
DeepSeek-V3 0324 supports 164K tokens and Nemotron Nano 9B v2 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 + Model License (Commercial use allowed) vs NVIDIA Open Model License Agreement ). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 0324 is developed by DeepSeek and Nemotron Nano 9B v2 is developed by NVIDIA.