Model Comparison

DeepSeek VL2 vs Nemotron Nano 9B v2Which is better in 2026?

Comparing DeepSeek VL2 and Nemotron Nano 9B v2 across benchmarks, pricing, and capabilities.

Verdict: DeepSeek VL2 vs Nemotron Nano 9B v2 — which is better?

DeepSeek VL2 (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.

Choose DeepSeek VL2 if…

  • you are already invested in the DeepSeek ecosystem

Choose Nemotron Nano 9B v2 if…

  • you want the most recent training data — it shipped Aug 2025

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and Nemotron Nano 9B v2don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

18.1B diff

DeepSeek VL2 has 18.1B more parameters than Nemotron Nano 9B v2, making it 203.4% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
NVIDIA
Nemotron Nano 9B v2
8.9Bparameters
27.0B
DeepSeek VL2
8.9B
Nemotron Nano 9B v2

Context Window

Maximum input and output token capacity

Only DeepSeek VL2 specifies input context (129,280 tokens). Only DeepSeek VL2 specifies output context (129,280 tokens).

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
NVIDIA
Nemotron Nano 9B v2
Input- tokens
Output- tokens
Mon Jul 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas Nemotron Nano 9B v2 does not.

DeepSeek VL2 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2

Text
Images
Audio
Video

Nemotron Nano 9B v2

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, 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 VL2

deepseek

Open weights

Nemotron Nano 9B v2

NVIDIA Open Model License Agreement

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Nemotron Nano 9B v2 was released on 2025-08-18.

Nemotron Nano 9B v2 is 8 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.6 years ago

Nemotron Nano 9B v2

Aug 18, 2025

11 months ago

8mo newer

Knowledge Cutoff

When training data ends

Nemotron Nano 9B v2 has a documented knowledge cutoff of 2024-09-01, while DeepSeek VL2'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 VL2's cutoff date.

DeepSeek VL2

—

Nemotron Nano 9B v2

Sep 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (129,280 tokens)
Supports multimodal inputs
NVIDIA

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

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek VL2 and Nemotron Nano 9B v2 side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Nemotron Nano 9B v2
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
NVIDIA
Nemotron Nano 9B v2

FAQ

Common questions about DeepSeek VL2 vs Nemotron Nano 9B v2.

Which is better, DeepSeek VL2 or Nemotron Nano 9B v2?

DeepSeek VL2 (DeepSeek) and Nemotron Nano 9B v2 (NVIDIA) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek VL2 compare to Nemotron Nano 9B v2 in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. 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 VL2 and Nemotron Nano 9B v2?

DeepSeek VL2 supports 129K 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 VL2 and Nemotron Nano 9B v2?

Key differences include multimodal support (yes vs no), licensing (deepseek vs NVIDIA Open Model License Agreement ). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Nemotron Nano 9B v2?

DeepSeek VL2 is developed by DeepSeek and Nemotron Nano 9B v2 is developed by NVIDIA.

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