Model Comparison

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

Phi-3.5-vision-instruct shows notably better performance in the majority of benchmarks.

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

DeepSeek VL2 Tiny (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 Tiny outperforms in 2 benchmarks (MathVista, TextVQA), while Phi-3.5-vision-instruct is better at 4 benchmarks (AI2D, ChartQA, MMBench, MMMU). Phi-3.5-vision-instruct shows notably better performance in the majority of benchmarks.

Choose DeepSeek VL2 Tiny if…

  • you want the most recent training data — it shipped Dec 2024

Choose Phi-3.5-vision-instruct if…

  • you want the strongest raw capability — it leads on 4 of 6 shared benchmarks
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

DeepSeek VL2 Tiny outperforms in 2 benchmarks (MathVista, TextVQA), while Phi-3.5-vision-instruct is better at 4 benchmarks (AI2D, ChartQA, MMBench, MMMU).

Phi-3.5-vision-instruct shows notably better performance in the majority of benchmarks.

Thu Jun 11 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

1.2B diff

Phi-3.5-vision-instruct has 1.2B more parameters than DeepSeek VL2 Tiny, making it 40.0% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
Microsoft
Phi-3.5-vision-instruct
4.2Bparameters
3.0B
DeepSeek VL2 Tiny
4.2B
Phi-3.5-vision-instruct

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 Tiny 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 Tiny

Text
Images
Audio
Video

Phi-3.5-vision-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny 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 Tiny

deepseek

Open weights

Phi-3.5-vision-instruct

MIT

Open weights

Release Timeline

When each model was launched

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

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

DeepSeek VL2 Tiny

Dec 13, 2024

1.5 years ago

3mo newer
Phi-3.5-vision-instruct

Aug 23, 2024

1.8 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 MathVista score (53.6% vs 43.9%)
Higher TextVQA score (80.7% vs 72.0%)
Microsoft
Higher AI2D score (78.1% vs 71.6%)
Higher ChartQA score (81.8% vs 81.0%)
Higher MMBench score (81.9% vs 69.2%)
Higher MMMU score (43.0% vs 40.7%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Tiny
Microsoft
Phi-3.5-vision-instruct

FAQ

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

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

Phi-3.5-vision-instruct shows notably better performance in the majority of benchmarks. DeepSeek VL2 Tiny 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 Tiny compare to Phi-3.5-vision-instruct in benchmarks?

DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. 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 Tiny 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 Tiny and Phi-3.5-vision-instruct?

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

Related comparisons