Phi 4 Mini vs Qwen3 VL 8B Thinking
Qwen3 VL 8B Thinking leads the LLM Stats Score 16.2 to -4.1.
Microsoft · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 8B Thinking leads the overall LLM Stats Score 16.2 to -4.1, ranking #227 overall.
In the 3 individual benchmarks reported for both models, Qwen3 VL 8B Thinking wins 3; 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 Phi 4 Mini
- you are already invested in the Microsoft ecosystem
Choose Qwen3 VL 8B Thinking
- overall performance matters — it scores 16.2 and ranks #227 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
17 reported for Phi 4 Mini · 50 for Qwen3 VL 8B Thinking
Phi 4 Mini outperforms in 0 benchmarks, while Qwen3 VL 8B Thinking is better at 3 benchmarks (GPQA, MMLU, MMLU-Pro).
Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3 VL 8B Thinking has 5.2B more parameters than Phi 4 Mini, making it 134.4% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 8B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 8B Thinking specifies output context (262,144 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3 VL 8B Thinking supports multimodal inputs, whereas Phi 4 Mini does not.
Qwen3 VL 8B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Phi 4 Mini
Qwen3 VL 8B Thinking
License
Usage and distribution terms
Phi 4 Mini is licensed under MIT, while Qwen3 VL 8B Thinking 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 Mini was released on 2025-02-01, while Qwen3 VL 8B Thinking was released on 2025-09-22.
Qwen3 VL 8B Thinking is 8 months newer than Phi 4 Mini.
Feb 1, 2025
1.6 years ago
Sep 22, 2025
12 months ago
7mo newerKnowledge Cutoff
When training data ends
Phi 4 Mini has a documented knowledge cutoff of 2024-06-01, while Qwen3 VL 8B Thinking's cutoff date is not specified.
We can confirm Phi 4 Mini's training data extends to 2024-06-01, but cannot make a direct comparison without Qwen3 VL 8B Thinking's cutoff date.
Jun 2024
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Outputs Comparison
Judge for yourself.
Run your own prompts against Phi 4 Mini and Qwen3 VL 8B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Phi 4 Mini vs Qwen3 VL 8B Thinking.