Model Comparison
Phi 4 vs Qwen3 VL 4B InstructWhich is better in 2026?
Both models are evenly matched across the benchmarks. Phi 4 is 2.6x cheaper per token.
Verdict: Phi 4 vs Qwen3 VL 4B Instruct — which is better?
Phi 4 (by Microsoft) and Qwen3 VL 4B Instruct (by Alibaba Cloud / Qwen Team) 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.
Phi 4 outperforms in 2 benchmarks (MMLU, MMLU-Pro), while Qwen3 VL 4B Instruct is better at 2 benchmarks (IFEval, SimpleQA). Both models are evenly matched across the benchmarks.
On price, Phi 4 is roughly 2.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 4B Instruct also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Choose Phi 4 if…
- cost matters — it's about 2.6x cheaper per token
Choose Qwen3 VL 4B Instruct if…
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
Phi 4 outperforms in 2 benchmarks (MMLU, MMLU-Pro), while Qwen3 VL 4B Instruct is better at 2 benchmarks (IFEval, SimpleQA).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Phi 4 ($0.07/1M tokens) is 1.4x cheaper than Qwen3 VL 4B Instruct ($0.10/1M tokens).
For output processing, Phi 4 ($0.14/1M tokens) is 4.3x cheaper than Qwen3 VL 4B Instruct ($0.60/1M tokens).
In conclusion, Qwen3 VL 4B Instruct is more expensive than Phi 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Phi 4 has 10.7B more parameters than Qwen3 VL 4B Instruct, making it 267.5% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 4B Instruct accepts 262,144 input tokens compared to Phi 4's 16,000 tokens. Qwen3 VL 4B Instruct can generate longer responses up to 262,144 tokens, while Phi 4 is limited to 16,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 4B Instruct supports multimodal inputs, whereas Phi 4 does not.
Qwen3 VL 4B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
Phi 4
Qwen3 VL 4B Instruct
License
Usage and distribution terms
Phi 4 is licensed under MIT, while Qwen3 VL 4B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Phi 4 was released on 2024-12-12, while Qwen3 VL 4B Instruct was released on 2025-09-22.
Qwen3 VL 4B Instruct is 9 months newer than Phi 4.
Dec 12, 2024
1.6 years ago
Sep 22, 2025
10 months ago
9mo newerKnowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while Qwen3 VL 4B Instruct's cutoff date is not specified.
We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without Qwen3 VL 4B Instruct's cutoff date.
Jun 2024
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Provider Availability
Phi 4 is available from DeepInfra. Qwen3 VL 4B Instruct is available from DeepInfra.
Phi 4
Qwen3 VL 4B Instruct
Outputs Comparison
Key Takeaways
Phi 4
View detailsMicrosoft
Qwen3 VL 4B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Phi 4 and Qwen3 VL 4B Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Phi 4 vs Qwen3 VL 4B Instruct.