Model Comparison

DeepSeek VL2 vs DeepSeek R1 Distill Qwen 14BWhich is better in 2026?

Comparing DeepSeek VL2 and DeepSeek R1 Distill Qwen 14B across benchmarks, pricing, and capabilities.

Verdict: DeepSeek VL2 vs DeepSeek R1 Distill Qwen 14B — which is better?

DeepSeek VL2 (by DeepSeek) and DeepSeek R1 Distill Qwen 14B (by DeepSeek) 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 DeepSeek R1 Distill Qwen 14B if…

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

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and DeepSeek R1 Distill Qwen 14Bdon'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

12.2B diff

DeepSeek VL2 has 12.2B more parameters than DeepSeek R1 Distill Qwen 14B, making it 82.4% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
DeepSeek
DeepSeek R1 Distill Qwen 14B
14.8Bparameters
27.0B
DeepSeek VL2
14.8B
DeepSeek R1 Distill Qwen 14B

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
DeepSeek
DeepSeek R1 Distill Qwen 14B
Input- tokens
Output- tokens
Mon Jul 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 14B 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

DeepSeek R1 Distill Qwen 14B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while DeepSeek R1 Distill Qwen 14B uses MIT.

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

DeepSeek VL2

deepseek

Open weights

DeepSeek R1 Distill Qwen 14B

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while DeepSeek R1 Distill Qwen 14B was released on 2025-01-20.

DeepSeek R1 Distill Qwen 14B is 1 month newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.6 years ago

DeepSeek R1 Distill Qwen 14B

Jan 20, 2025

1.5 years ago

1mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

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

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 DeepSeek R1 Distill Qwen 14B side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
DeepSeek R1 Distill Qwen 14B
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
DeepSeek
DeepSeek R1 Distill Qwen 14B

FAQ

Common questions about DeepSeek VL2 vs DeepSeek R1 Distill Qwen 14B.

Which is better, DeepSeek VL2 or DeepSeek R1 Distill Qwen 14B?

DeepSeek VL2 (DeepSeek) and DeepSeek R1 Distill Qwen 14B (DeepSeek) 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 DeepSeek R1 Distill Qwen 14B in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. DeepSeek R1 Distill Qwen 14B scores MATH-500: 93.9%, AIME 2024: 80.0%, GPQA: 59.1%, LiveCodeBench: 53.1%.

What are the context window sizes for DeepSeek VL2 and DeepSeek R1 Distill Qwen 14B?

DeepSeek VL2 supports 129K tokens and DeepSeek R1 Distill Qwen 14B 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 DeepSeek R1 Distill Qwen 14B?

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

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