Model Comparison

DeepSeek VL2 vs DeepSeek R1 Zero

Comparing DeepSeek VL2 and DeepSeek R1 Zero across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and DeepSeek R1 Zero don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Apr 21 2026 • llm-stats.com
DeepSeek
DeepSeek VL2
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
DeepSeek
DeepSeek R1 Zero
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

644.0B diff

DeepSeek R1 Zero has 644.0B more parameters than DeepSeek VL2, making it 2385.2% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
DeepSeek
DeepSeek R1 Zero
671.0Bparameters
27.0B
DeepSeek VL2
671.0B
DeepSeek R1 Zero

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 Zero
Input- tokens
Output- tokens
Tue Apr 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas DeepSeek R1 Zero 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 Zero

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while DeepSeek R1 Zero 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 Zero

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while DeepSeek R1 Zero was released on 2025-01-20.

DeepSeek R1 Zero is 1 month newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.4 years ago

DeepSeek R1 Zero

Jan 20, 2025

1.2 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

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Key Takeaways

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
DeepSeek
DeepSeek R1 Zero

FAQ

Common questions about DeepSeek VL2 vs DeepSeek R1 Zero

DeepSeek VL2 (DeepSeek) and DeepSeek R1 Zero (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%.
DeepSeek VL2 supports 129K tokens and DeepSeek R1 Zero supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (yes vs no), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.