Model Comparison

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

DeepSeek VL2 has a slight edge in benchmark performance.

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

DeepSeek VL2 (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 outperforms in 5 benchmarks (ChartQA, DocVQA, InfoVQA, MathVista, TextVQA), while Phi-4-multimodal-instruct is better at 4 benchmarks (AI2D, MMBench, MMMU, OCRBench). DeepSeek VL2 has a slight edge in benchmark performance.

DeepSeek VL2 also accepts a larger context window (129,280 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek VL2 if…

  • you want the strongest raw capability — it leads on 5 of 9 shared benchmarks
  • you process long inputs — it offers a 129,280 token context window

Choose Phi-4-multimodal-instruct if…

  • you want the most recent training data — it shipped Feb 2025

Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

DeepSeek VL2 outperforms in 5 benchmarks (ChartQA, DocVQA, InfoVQA, MathVista, TextVQA), while Phi-4-multimodal-instruct is better at 4 benchmarks (AI2D, MMBench, MMMU, OCRBench).

DeepSeek VL2 has a slight edge in benchmark performance.

Sun Jul 19 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

21.4B diff

DeepSeek VL2 has 21.4B more parameters than Phi-4-multimodal-instruct, making it 382.1% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Microsoft
Phi-4-multimodal-instruct
5.6Bparameters
27.0B
DeepSeek VL2
5.6B
Phi-4-multimodal-instruct

Context Window

Maximum input and output token capacity

DeepSeek VL2 accepts 129,280 input tokens compared to Phi-4-multimodal-instruct's 128,000 tokens. DeepSeek VL2 can generate longer responses up to 129,280 tokens, while Phi-4-multimodal-instruct is limited to 128,000 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 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 and Phi-4-multimodal-instruct support multimodal inputs.

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

DeepSeek VL2

Text
Images
Audio
Video

Phi-4-multimodal-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 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

deepseek

Open weights

Phi-4-multimodal-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 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.

DeepSeek VL2

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'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's cutoff date.

DeepSeek VL2

—

Phi-4-multimodal-instruct

Jun 2024

Provider Availability

DeepSeek VL2 is available from Replicate. Phi-4-multimodal-instruct is available from DeepInfra.

DeepSeek VL2

replicate logo
Replicate

Phi-4-multimodal-instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.10/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (129,280 tokens)
Higher ChartQA score (86.0% vs 81.4%)
Higher DocVQA score (93.3% vs 93.2%)
Higher InfoVQA score (78.1% vs 72.7%)
Higher MathVista score (62.8% vs 62.4%)
Higher TextVQA score (84.2% vs 75.6%)
Microsoft
Higher AI2D score (82.3% vs 81.4%)
Higher MMBench score (86.7% vs 79.6%)
Higher MMMU score (55.1% vs 51.1%)
Higher OCRBench score (84.4% vs 81.1%)

Detailed Comparison

Interactive Arena

Judge for yourself.

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

DeepSeek VL2
✓ Preferred
Phi-4-multimodal-instruct
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
Microsoft
Phi-4-multimodal-instruct

FAQ

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

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

DeepSeek VL2 has a slight edge in benchmark performance. DeepSeek VL2 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 compare to Phi-4-multimodal-instruct in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. 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 and Phi-4-multimodal-instruct?

DeepSeek VL2 supports 129K 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 and Phi-4-multimodal-instruct?

Key differences include context window (129K vs 128K), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.

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

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

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