Phi-4-multimodal-instruct vs Qwen3 VL 32B Thinking
Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.
Microsoft · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Phi-4-multimodal-instruct outperforms in 0 benchmarks, while Qwen3 VL 32B Thinking is better at 4 benchmarks (AI2D, BLINK, MMMU-Pro, OCRBench). Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Phi-4-multimodal-instruct
- you want predictable pricing at $0.05/M input and $0.10/M output
Choose Qwen3 VL 32B Thinking
- you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Phi-4-multimodal-instruct outperforms in 0 benchmarks, while Qwen3 VL 32B Thinking is better at 4 benchmarks (AI2D, BLINK, MMMU-Pro, OCRBench).
Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Model Size
Parameter count comparison
Qwen3 VL 32B Thinking has 27.4B more parameters than Phi-4-multimodal-instruct, making it 489.3% larger.
Context Window
Maximum input and output token capacity
Only Phi-4-multimodal-instruct specifies input context (128,000 tokens). Only Phi-4-multimodal-instruct specifies output context (128,000 tokens).
Input Capabilities
Supported data types and modalities
Both Phi-4-multimodal-instruct and Qwen3 VL 32B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Phi-4-multimodal-instruct
Qwen3 VL 32B Thinking
License
Usage and distribution terms
Phi-4-multimodal-instruct is licensed under MIT, while Qwen3 VL 32B 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-multimodal-instruct was released on 2025-02-01, while Qwen3 VL 32B Thinking was released on 2025-09-22.
Qwen3 VL 32B Thinking is 8 months newer than Phi-4-multimodal-instruct.
Feb 1, 2025
1.6 years ago
Sep 22, 2025
11 months ago
7mo newerKnowledge Cutoff
When training data ends
Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while Qwen3 VL 32B Thinking's cutoff date is not specified.
We can confirm Phi-4-multimodal-instruct's training data extends to 2024-06-01, but cannot make a direct comparison without Qwen3 VL 32B Thinking's cutoff date.
Jun 2024
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Outputs Comparison
Judge for yourself.
Run your own prompts against Phi-4-multimodal-instruct and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Phi-4-multimodal-instruct vs Qwen3 VL 32B Thinking.