Model Comparison

DeepSeek-V3 vs DeepSeek VL2

Comparing DeepSeek-V3 and DeepSeek VL2 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3 and DeepSeek VL2 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
Thu Apr 30 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
DeepSeek
DeepSeek VL2
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-V3 has 644.0B more parameters than DeepSeek VL2, making it 2385.2% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
DeepSeek
DeepSeek VL2
27.0Bparameters
671.0B
DeepSeek-V3
27.0B
DeepSeek VL2

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to DeepSeek VL2's 129,280 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Thu Apr 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas DeepSeek-V3 does not.

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

DeepSeek-V3

Text
Images
Audio
Video

DeepSeek VL2

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while DeepSeek VL2 uses deepseek.

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

DeepSeek VL2

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while DeepSeek VL2 was released on 2024-12-13.

DeepSeek-V3 is 0 month newer than DeepSeek VL2.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

1w newer
DeepSeek VL2

Dec 13, 2024

1.4 years ago

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

Provider Availability

DeepSeek-V3 is available from DeepSeek. DeepSeek VL2 is available from Replicate.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

DeepSeek VL2

replicate logo
Replicate
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
DeepSeek
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
DeepSeek
DeepSeek VL2

FAQ

Common questions about DeepSeek-V3 vs DeepSeek VL2

DeepSeek-V3 (DeepSeek) and DeepSeek VL2 (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%.
DeepSeek-V3 supports 131K tokens and DeepSeek VL2 supports 129K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 129K), multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs deepseek). See the full comparison above for benchmark-by-benchmark results.