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DeepSeek-V3 vs Nemotron Nano 9B v2

Nemotron Nano 9B v2 significantly outperforms across most benchmarks.

DeepSeek · NVIDIA · Updated for 2026

Which is better?

DeepSeek-V3 outperforms in 0 benchmarks, while Nemotron Nano 9B v2 is better at 4 benchmarks (GPQA, IFEval, LiveCodeBench, MATH-500). Nemotron Nano 9B v2 significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-V3

  • you want predictable pricing at $0.27/M input and $1.10/M output

Choose Nemotron Nano 9B v2

  • you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
  • you want the most recent training data — it shipped Aug 2025

At a glance

The differences that matter most.

DeepSeek-V3
DeepSeek
Nemotron Nano 9B v2
NVIDIA
Benchmark wins
0 of 4
4 of 4
Input price
$0.27 / M
— / M
Output price
$1.10 / M
— / M
Context window
131,072
—
Released
Dec 2024
Aug 2025
License
MIT + Model License (Commercial use allowed)
NVIDIA Open Model License Agreement

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V3 outperforms in 0 benchmarks, while Nemotron Nano 9B v2 is better at 4 benchmarks (GPQA, IFEval, LiveCodeBench, MATH-500).

Nemotron Nano 9B v2 significantly outperforms across most benchmarks.

Mon Aug 24 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

662.1B diff

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

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

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
NVIDIA
Nemotron Nano 9B v2
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 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

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 was released on 2024-12-25, while Nemotron Nano 9B v2 was released on 2025-08-18.

Nemotron Nano 9B v2 is 8 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.7 years ago

Nemotron Nano 9B v2

Aug 18, 2025

1.0 years ago

7mo newer

Knowledge Cutoff

When training data ends

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

DeepSeek-V3

—

Nemotron Nano 9B v2

Sep 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3 and Nemotron Nano 9B v2 side-by-side, then vote on the output you prefer.

DeepSeek-V3
✓ Preferred
Nemotron Nano 9B v2
Open in Playground

FAQ

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

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

Nemotron Nano 9B v2 significantly outperforms across most benchmarks. DeepSeek-V3 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 compare to Nemotron Nano 9B v2 in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. 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 and Nemotron Nano 9B v2?

DeepSeek-V3 supports 131K 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 and Nemotron Nano 9B v2?

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.

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

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

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