Model Comparison

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

Phi-4-multimodal-instruct significantly outperforms across most benchmarks.

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

DeepSeek VL2 Tiny (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 Tiny outperforms in 1 benchmarks (TextVQA), while Phi-4-multimodal-instruct is better at 8 benchmarks (AI2D, ChartQA, DocVQA, InfoVQA, MathVista, MMBench, MMMU, OCRBench). Phi-4-multimodal-instruct significantly outperforms across most benchmarks.

Choose DeepSeek VL2 Tiny if…

  • you are already invested in the DeepSeek ecosystem

Choose Phi-4-multimodal-instruct if…

  • you want the strongest raw capability — it leads on 8 of 9 shared benchmarks
  • you want the most recent training data — it shipped Feb 2025
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

DeepSeek VL2 Tiny outperforms in 1 benchmarks (TextVQA), while Phi-4-multimodal-instruct is better at 8 benchmarks (AI2D, ChartQA, DocVQA, InfoVQA, MathVista, MMBench, MMMU, OCRBench).

Phi-4-multimodal-instruct significantly outperforms across most benchmarks.

Fri Jun 12 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

2.6B diff

Phi-4-multimodal-instruct has 2.6B more parameters than DeepSeek VL2 Tiny, making it 86.7% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
Microsoft
Phi-4-multimodal-instruct
5.6Bparameters
3.0B
DeepSeek VL2 Tiny
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 Tiny
Input- tokens
Output- tokens
Microsoft
Phi-4-multimodal-instruct
Input128,000 tokens
Output128,000 tokens
Fri Jun 12 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

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

DeepSeek VL2 Tiny

Text
Images
Audio
Video

Phi-4-multimodal-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny 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 Tiny

deepseek

Open weights

Phi-4-multimodal-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny 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 Tiny.

DeepSeek VL2 Tiny

Dec 13, 2024

1.5 years ago

Phi-4-multimodal-instruct

Feb 1, 2025

1.4 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 Tiny'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 Tiny's cutoff date.

DeepSeek VL2 Tiny

—

Phi-4-multimodal-instruct

Jun 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Higher TextVQA score (80.7% vs 75.6%)
Microsoft
Larger context window (128,000 tokens)
Higher AI2D score (82.3% vs 71.6%)
Higher ChartQA score (81.4% vs 81.0%)
Higher DocVQA score (93.2% vs 88.9%)
Higher InfoVQA score (72.7% vs 66.1%)
Higher MathVista score (62.4% vs 53.6%)
Higher MMBench score (86.7% vs 69.2%)
Higher MMMU score (55.1% vs 40.7%)
Higher OCRBench score (84.4% vs 80.9%)

Detailed Comparison

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

FAQ

Common questions about DeepSeek VL2 Tiny vs Phi-4-multimodal-instruct.

Which is better, DeepSeek VL2 Tiny or Phi-4-multimodal-instruct?

Phi-4-multimodal-instruct significantly outperforms across most benchmarks. DeepSeek VL2 Tiny 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 Tiny compare to Phi-4-multimodal-instruct in benchmarks?

DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. 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 Tiny and Phi-4-multimodal-instruct?

DeepSeek VL2 Tiny 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 Tiny 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 Tiny and Phi-4-multimodal-instruct?

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

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