Model Comparison

DeepSeek VL2 Small vs Phi-4-multimodal-instructWhich is better in 2026?

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

Verdict: DeepSeek VL2 Small vs Phi-4-multimodal-instruct — which is better?

DeepSeek VL2 Small (by DeepSeek) and Phi-4-multimodal-instruct (by Microsoft) 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.

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.

Choose DeepSeek VL2 Small if…

  • you are already invested in the DeepSeek ecosystem

Choose Phi-4-multimodal-instruct if…

  • you want the strongest raw capability — it leads on 6 of 9 shared benchmarks
  • you want the most recent training data — it shipped Feb 2025

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.

Sun Jul 19 2026 • llm-stats.com

Arena Performance

Human preference votes

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
Sun Jul 19 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

1.6 years ago

Phi-4-multimodal-instruct

Feb 1, 2025

1.5 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

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek VL2 Small and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.

DeepSeek VL2 Small
✓ Preferred
Phi-4-multimodal-instruct
Open in Playground
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.

Which is better, DeepSeek VL2 Small or 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.

How does DeepSeek VL2 Small compare to Phi-4-multimodal-instruct in benchmarks?

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%.

What are the context window sizes for DeepSeek VL2 Small and Phi-4-multimodal-instruct?

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.

What are the main differences between DeepSeek VL2 Small and Phi-4-multimodal-instruct?

Key differences include licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 Small and Phi-4-multimodal-instruct?

DeepSeek VL2 Small is developed by DeepSeek and Phi-4-multimodal-instruct is developed by Microsoft.

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