Model Comparison

DeepSeek-V3.2-Exp vs Nemotron Nano 9B v2Which is better in 2026?

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

Verdict: DeepSeek-V3.2-Exp vs Nemotron Nano 9B v2 — which is better?

DeepSeek-V3.2-Exp (by DeepSeek) and Nemotron Nano 9B v2 (by NVIDIA) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

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.

Choose DeepSeek-V3.2-Exp if…

  • you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
  • you want the most recent training data — it shipped Sep 2025

Choose Nemotron Nano 9B v2 if…

  • you are already invested in the NVIDIA ecosystem
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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.

Sat Jun 13 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
Sat Jun 13 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

8 months ago

1mo newer
Nemotron Nano 9B v2

Aug 18, 2025

9 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.

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