Phi-3.5-mini-instruct vs Qwen3.5-2B
Qwen3.5-2B leads the LLM Stats Score 3.9 to -3.8.
Microsoft · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3.5-2B leads the overall LLM Stats Score 3.9 to -3.8, ranking #303 overall.
In the 3 individual benchmarks reported for both models, Qwen3.5-2B 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-3.5-mini-instruct
- you want predictable pricing at $0.10/M input and $0.10/M output
Choose Qwen3.5-2B
- overall performance matters — it scores 3.9 and ranks #303 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 Mar 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
31 reported for Phi-3.5-mini-instruct · 20 for Qwen3.5-2B
Phi-3.5-mini-instruct outperforms in 0 benchmarks, while Qwen3.5-2B is better at 3 benchmarks (GPQA, MMLU-Pro, MMMLU).
Qwen3.5-2B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Phi-3.5-mini-instruct has 1.8B more parameters than Qwen3.5-2B, making it 90.0% larger.
Context Window
Maximum input and output token capacity
Only Phi-3.5-mini-instruct specifies input context (128,000 tokens). Only Phi-3.5-mini-instruct specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3.5-2B supports multimodal inputs, whereas Phi-3.5-mini-instruct does not.
Qwen3.5-2B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Phi-3.5-mini-instruct
Qwen3.5-2B
License
Usage and distribution terms
Phi-3.5-mini-instruct is licensed under MIT, while Qwen3.5-2B 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-3.5-mini-instruct was released on 2024-08-23, while Qwen3.5-2B was released on 2026-03-02.
Qwen3.5-2B is 19 months newer than Phi-3.5-mini-instruct.
Aug 23, 2024
2.0 years ago
Mar 2, 2026
6 months ago
1.5yr newerKnowledge 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 Phi-3.5-mini-instruct and Qwen3.5-2B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Phi-3.5-mini-instruct vs Qwen3.5-2B.