Model Comparison

DeepSeek VL2 Small vs Phi-4-multimodal-instruct

Phi-4-multimodal-instruct shows notably better performance in the majority of benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

DeepSeek VL2 Small outperforms in 3 benchmarks (ChartQA, InfoVQA, TextVQA), while Phi-4-multimodal-instruct is better at 6 benchmarks (AI2D, DocVQA, MathVista, MMBench, MMMU, OCRBench).

Phi-4-multimodal-instruct shows notably better performance in the majority of benchmarks.

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
DeepSeek
DeepSeek VL2 Small
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Microsoft
Phi-4-multimodal-instruct
Input tokens$0.05
Output tokens$0.10
Best providerDeepinfra
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Model Size

Parameter count comparison

10.4B diff

DeepSeek VL2 Small has 10.4B more parameters than Phi-4-multimodal-instruct, making it 185.7% larger.

DeepSeek
DeepSeek VL2 Small
16.0Bparameters
Microsoft
Phi-4-multimodal-instruct
5.6Bparameters
16.0B
DeepSeek VL2 Small
5.6B
Phi-4-multimodal-instruct

Context Window

Maximum input and output token capacity

Only Phi-4-multimodal-instruct specifies input context (128,000 tokens). Only Phi-4-multimodal-instruct specifies output context (128,000 tokens).

DeepSeek
DeepSeek VL2 Small
Input- tokens
Output- tokens
Microsoft
Phi-4-multimodal-instruct
Input128,000 tokens
Output128,000 tokens
Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 Small and Phi-4-multimodal-instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek VL2 Small

Text
Images
Audio
Video

Phi-4-multimodal-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Small is licensed under deepseek, while Phi-4-multimodal-instruct uses MIT.

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

DeepSeek VL2 Small

deepseek

Open weights

Phi-4-multimodal-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Small was released on 2024-12-13, while Phi-4-multimodal-instruct was released on 2025-02-01.

Phi-4-multimodal-instruct is 2 months newer than DeepSeek VL2 Small.

DeepSeek VL2 Small

Dec 13, 2024

1.3 years ago

Phi-4-multimodal-instruct

Feb 1, 2025

1.2 years ago

1mo newer

Knowledge Cutoff

When training data ends

Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while DeepSeek VL2 Small's cutoff date is not specified.

We can confirm Phi-4-multimodal-instruct's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek VL2 Small's cutoff date.

DeepSeek VL2 Small

—

Phi-4-multimodal-instruct

Jun 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Higher ChartQA score (84.5% vs 81.4%)
Higher InfoVQA score (75.8% vs 72.7%)
Higher TextVQA score (83.4% vs 75.6%)
Microsoft
Larger context window (128,000 tokens)
Higher AI2D score (82.3% vs 80.0%)
Higher DocVQA score (93.2% vs 92.3%)
Higher MathVista score (62.4% vs 60.7%)
Higher MMBench score (86.7% vs 80.3%)
Higher MMMU score (55.1% vs 48.0%)
Higher OCRBench score (84.4% vs 83.4%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Small
Microsoft
Phi-4-multimodal-instruct

FAQ

Common questions about DeepSeek VL2 Small vs Phi-4-multimodal-instruct

Phi-4-multimodal-instruct shows notably better performance in the majority of benchmarks. DeepSeek VL2 Small is made by DeepSeek and Phi-4-multimodal-instruct is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek VL2 Small scores DocVQA: 92.3%, ChartQA: 84.5%, OCRBench: 83.4%, TextVQA: 83.4%, MMBench: 80.3%. Phi-4-multimodal-instruct scores ScienceQA Visual: 97.5%, DocVQA: 93.2%, MMBench: 86.7%, POPE: 85.6%, OCRBench: 84.4%.
DeepSeek VL2 Small supports an unknown number of tokens and Phi-4-multimodal-instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.
DeepSeek VL2 Small is developed by DeepSeek and Phi-4-multimodal-instruct is developed by Microsoft.