Model Comparison

DeepSeek-V3.2-Exp vs Nemotron Nano 9B v2

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3.2-Exp outperforms in 3 benchmarks (AIME 2025, GPQA, LiveCodeBench), while Nemotron Nano 9B v2 is better at 0 benchmarks.

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

Thu May 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

676.1B diff

DeepSeek-V3.2-Exp has 676.1B more parameters than Nemotron Nano 9B v2, making it 7596.6% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
NVIDIA
Nemotron Nano 9B v2
8.9Bparameters
685.0B
DeepSeek-V3.2-Exp
8.9B
Nemotron Nano 9B v2

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Exp specifies input context (163,840 tokens). Only DeepSeek-V3.2-Exp specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
NVIDIA
Nemotron Nano 9B v2
Input- tokens
Output- tokens
Thu May 14 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Exp is licensed under MIT, 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-V3.2-Exp

MIT

Open weights

Nemotron Nano 9B v2

NVIDIA Open Model License Agreement

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Nemotron Nano 9B v2 was released on 2025-08-18.

DeepSeek-V3.2-Exp is 1 month newer than Nemotron Nano 9B v2.

DeepSeek-V3.2-Exp

Sep 29, 2025

7 months ago

1mo newer
Nemotron Nano 9B v2

Aug 18, 2025

8 months ago

Knowledge Cutoff

When training data ends

Nemotron Nano 9B v2 has a documented knowledge cutoff of 2024-09-01, while DeepSeek-V3.2-Exp'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-V3.2-Exp's cutoff date.

DeepSeek-V3.2-Exp

—

Nemotron Nano 9B v2

Sep 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Higher AIME 2025 score (89.3% vs 72.1%)
Higher GPQA score (79.9% vs 64.0%)
Higher LiveCodeBench score (74.1% vs 71.1%)
NVIDIA

No standout differentiators in the data we have for this pair.

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
NVIDIA
Nemotron Nano 9B v2

FAQ

Common questions about DeepSeek-V3.2-Exp vs Nemotron Nano 9B v2.

Which is better, DeepSeek-V3.2-Exp or Nemotron Nano 9B v2?

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp 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.

How does DeepSeek-V3.2-Exp compare to Nemotron Nano 9B v2 in benchmarks?

DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. Nemotron Nano 9B v2 scores MATH-500: 97.8%, IFEval: 90.3%, AIME 2025: 72.1%, LiveCodeBench: 71.1%, BFCL_v3_MultiTurn: 66.9%.

What are the context window sizes for DeepSeek-V3.2-Exp and Nemotron Nano 9B v2?

DeepSeek-V3.2-Exp 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.

What are the main differences between DeepSeek-V3.2-Exp and Nemotron Nano 9B v2?

Key differences include licensing (MIT vs NVIDIA Open Model License Agreement ). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2-Exp and Nemotron Nano 9B v2?

DeepSeek-V3.2-Exp is developed by DeepSeek and Nemotron Nano 9B v2 is developed by NVIDIA.