DeepSeek VL2 Small vs Phi-3.5-vision-instruct
DeepSeek VL2 Small and Phi-3.5-vision-instruct are closely matched at 1.2 and -3.4 on the LLM Stats Score.
DeepSeek · Microsoft · Updated for 2026
Which is better?
DeepSeek VL2 Small and Phi-3.5-vision-instruct are closely matched on the overall LLM Stats Score at 1.2 and -3.4.
In the 6 individual benchmarks reported for both models, DeepSeek VL2 Small wins 5; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek VL2 Small
- you value its reported benchmark strengths — it wins 5 of 6 exact shared results
- you want the most recent training data — it shipped Dec 2024
Choose Phi-3.5-vision-instruct
- you are already invested in the Microsoft ecosystem
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
14 reported for DeepSeek VL2 Small · 9 for Phi-3.5-vision-instruct
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.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek VL2 Small has 11.8B more parameters than Phi-3.5-vision-instruct, making it 281.0% larger.
Input capabilities
Documented input modalities across available providers
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
Phi-3.5-vision-instruct
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
Open weights
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.
Dec 13, 2024
1.7 years ago
3mo newerAug 23, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
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.
FAQ
Common questions about DeepSeek VL2 Small vs Phi-3.5-vision-instruct.