Model Comparison

DeepSeek VL2 vs Llama 3.1 Nemotron Nano 8B V1Which is better in 2026?

Comparing DeepSeek VL2 and Llama 3.1 Nemotron Nano 8B V1 across benchmarks, pricing, and capabilities.

Verdict: DeepSeek VL2 vs Llama 3.1 Nemotron Nano 8B V1 — which is better?

DeepSeek VL2 (by DeepSeek) and Llama 3.1 Nemotron Nano 8B V1 (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 Llama 3.1 Nemotron Nano 8B V1 if…

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

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and Llama 3.1 Nemotron Nano 8B V1don'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

19.0B diff

DeepSeek VL2 has 19.0B more parameters than Llama 3.1 Nemotron Nano 8B V1, making it 237.5% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
NVIDIA
Llama 3.1 Nemotron Nano 8B V1
8.0Bparameters
27.0B
DeepSeek VL2
8.0B
Llama 3.1 Nemotron Nano 8B V1

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
Llama 3.1 Nemotron Nano 8B V1
Input- tokens
Output- tokens
Sat Jun 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas Llama 3.1 Nemotron Nano 8B V1 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

Llama 3.1 Nemotron Nano 8B V1

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Llama 3.1 Nemotron Nano 8B V1 uses Llama 3.1 Community License.

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

DeepSeek VL2

deepseek

Open weights

Llama 3.1 Nemotron Nano 8B V1

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Llama 3.1 Nemotron Nano 8B V1 was released on 2025-03-18.

Llama 3.1 Nemotron Nano 8B V1 is 3 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.5 years ago

Llama 3.1 Nemotron Nano 8B V1

Mar 18, 2025

1.3 years ago

3mo newer

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron Nano 8B V1 has a documented knowledge cutoff of 2023-12-31, while DeepSeek VL2's cutoff date is not specified.

We can confirm Llama 3.1 Nemotron Nano 8B V1's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek VL2's cutoff date.

DeepSeek VL2

—

Llama 3.1 Nemotron Nano 8B V1

Dec 2023

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 Llama 3.1 Nemotron Nano 8B V1 side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Llama 3.1 Nemotron Nano 8B V1
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
NVIDIA
Llama 3.1 Nemotron Nano 8B V1

FAQ

Common questions about DeepSeek VL2 vs Llama 3.1 Nemotron Nano 8B V1.

Which is better, DeepSeek VL2 or Llama 3.1 Nemotron Nano 8B V1?

DeepSeek VL2 (DeepSeek) and Llama 3.1 Nemotron Nano 8B V1 (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 Llama 3.1 Nemotron Nano 8B V1 in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Llama 3.1 Nemotron Nano 8B V1 scores MATH-500: 95.4%, MBPP: 84.6%, MT-Bench: 81.0%, IFEval: 79.3%, BFCL v2: 63.6%.

What are the context window sizes for DeepSeek VL2 and Llama 3.1 Nemotron Nano 8B V1?

DeepSeek VL2 supports 129K tokens and Llama 3.1 Nemotron Nano 8B V1 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 Llama 3.1 Nemotron Nano 8B V1?

Key differences include multimodal support (yes vs no), licensing (deepseek vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Llama 3.1 Nemotron Nano 8B V1?

DeepSeek VL2 is developed by DeepSeek and Llama 3.1 Nemotron Nano 8B V1 is developed by NVIDIA.

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