Model Comparison

DeepSeek VL2 Small vs Phi-3.5-vision-instructWhich is better in 2026?

DeepSeek VL2 Small significantly outperforms across most benchmarks.

Verdict: DeepSeek VL2 Small vs Phi-3.5-vision-instruct — which is better?

DeepSeek VL2 Small (by DeepSeek) and Phi-3.5-vision-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 5 benchmarks (AI2D, ChartQA, MathVista, MMMU, TextVQA), while Phi-3.5-vision-instruct is better at 1 benchmark (MMBench). DeepSeek VL2 Small significantly outperforms across most benchmarks.

Choose DeepSeek VL2 Small if…

  • you want the strongest raw capability — it leads on 5 of 6 shared benchmarks
  • you want the most recent training data — it shipped Dec 2024

Choose Phi-3.5-vision-instruct if…

  • you are already invested in the Microsoft ecosystem

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

DeepSeek VL2 Small outperforms in 5 benchmarks (AI2D, ChartQA, MathVista, MMMU, TextVQA), while Phi-3.5-vision-instruct is better at 1 benchmark (MMBench).

DeepSeek VL2 Small significantly outperforms across most benchmarks.

Sun Jul 19 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

11.8B diff

DeepSeek VL2 Small has 11.8B more parameters than Phi-3.5-vision-instruct, making it 281.0% larger.

DeepSeek
DeepSeek VL2 Small
16.0Bparameters
Microsoft
Phi-3.5-vision-instruct
4.2Bparameters
16.0B
DeepSeek VL2 Small
4.2B
Phi-3.5-vision-instruct

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 Small and Phi-3.5-vision-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-3.5-vision-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Small is licensed under deepseek, while Phi-3.5-vision-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-3.5-vision-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Small was released on 2024-12-13, while Phi-3.5-vision-instruct was released on 2024-08-23.

DeepSeek VL2 Small is 4 months newer than Phi-3.5-vision-instruct.

DeepSeek VL2 Small

Dec 13, 2024

1.6 years ago

3mo newer
Phi-3.5-vision-instruct

Aug 23, 2024

1.9 years ago

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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Higher AI2D score (80.0% vs 78.1%)
Higher ChartQA score (84.5% vs 81.8%)
Higher MathVista score (60.7% vs 43.9%)
Higher MMMU score (48.0% vs 43.0%)
Higher TextVQA score (83.4% vs 72.0%)
Microsoft
Higher MMBench score (81.9% vs 80.3%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek VL2 Small and Phi-3.5-vision-instruct side-by-side, then vote on the output you prefer.

DeepSeek VL2 Small
✓ Preferred
Phi-3.5-vision-instruct
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Small
Microsoft
Phi-3.5-vision-instruct

FAQ

Common questions about DeepSeek VL2 Small vs Phi-3.5-vision-instruct.

Which is better, DeepSeek VL2 Small or Phi-3.5-vision-instruct?

DeepSeek VL2 Small significantly outperforms across most benchmarks. DeepSeek VL2 Small is made by DeepSeek and Phi-3.5-vision-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-3.5-vision-instruct in benchmarks?

DeepSeek VL2 Small scores DocVQA: 92.3%, ChartQA: 84.5%, OCRBench: 83.4%, TextVQA: 83.4%, MMBench: 80.3%. Phi-3.5-vision-instruct scores ScienceQA: 91.3%, POPE: 86.1%, MMBench: 81.9%, ChartQA: 81.8%, AI2D: 78.1%.

What are the main differences between DeepSeek VL2 Small and Phi-3.5-vision-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-3.5-vision-instruct?

DeepSeek VL2 Small is developed by DeepSeek and Phi-3.5-vision-instruct is developed by Microsoft.

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