Model Comparison

DeepSeek VL2 vs DeepSeek-R1-0528

Comparing DeepSeek VL2 and DeepSeek-R1-0528 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and DeepSeek-R1-0528 don'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

644.0B diff

DeepSeek-R1-0528 has 644.0B more parameters than DeepSeek VL2, making it 2385.2% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
DeepSeek
DeepSeek-R1-0528
671.0Bparameters
27.0B
DeepSeek VL2
671.0B
DeepSeek-R1-0528

Context Window

Maximum input and output token capacity

DeepSeek-R1-0528 accepts 131,072 input tokens compared to DeepSeek VL2's 129,280 tokens. DeepSeek-R1-0528 can generate longer responses up to 131,072 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Tue May 12 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas DeepSeek-R1-0528 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-R1-0528

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while DeepSeek-R1-0528 uses MIT.

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

DeepSeek VL2

deepseek

Open weights

DeepSeek-R1-0528

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while DeepSeek-R1-0528 was released on 2025-05-28.

DeepSeek-R1-0528 is 6 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.4 years ago

DeepSeek-R1-0528

May 28, 2025

11 months ago

5mo 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

Provider Availability

DeepSeek VL2 is available from Replicate. DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita.

DeepSeek VL2

replicate logo
Replicate

DeepSeek-R1-0528

deepinfra logo
Deepinfra
Input Price:Input: $0.50/1MOutput Price:Output: $2.15/1M
deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.70/1MOutput Price:Output: $2.50/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
DeepSeek
DeepSeek-R1-0528

FAQ

Common questions about DeepSeek VL2 vs DeepSeek-R1-0528.

Which is better, DeepSeek VL2 or DeepSeek-R1-0528?

DeepSeek VL2 (DeepSeek) and DeepSeek-R1-0528 (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-R1-0528 in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%.

What are the context window sizes for DeepSeek VL2 and DeepSeek-R1-0528?

DeepSeek VL2 supports 129K tokens and DeepSeek-R1-0528 supports 131K 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-R1-0528?

Key differences include context window (129K vs 131K), multimodal support (yes vs no), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.