Phi-3.5-mini-instruct vs Qwen2.5-Omni-7B
Qwen2.5-Omni-7B leads the LLM Stats Score 5.2 to -3.8.
Microsoft · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen2.5-Omni-7B leads the overall LLM Stats Score 5.2 to -3.8, ranking #315 overall.
In the 6 individual benchmarks reported for both models, Qwen2.5-Omni-7B 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 Phi-3.5-mini-instruct
- you want predictable pricing at $0.10/M input and $0.10/M output
Choose Qwen2.5-Omni-7B
- overall performance matters — it scores 5.2 and ranks #315 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 5 of 6 exact shared results
- you want the most recent training data — it shipped Mar 2025
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 · 45 for Qwen2.5-Omni-7B
Phi-3.5-mini-instruct outperforms in 1 benchmarks (MMLU-Pro), while Qwen2.5-Omni-7B is better at 5 benchmarks (GPQA, GSM8k, HumanEval, MATH, MBPP).
Qwen2.5-Omni-7B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen2.5-Omni-7B has 3.2B more parameters than Phi-3.5-mini-instruct, making it 84.2% 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
Qwen2.5-Omni-7B supports multimodal inputs, whereas Phi-3.5-mini-instruct does not.
Qwen2.5-Omni-7B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Phi-3.5-mini-instruct
Qwen2.5-Omni-7B
License
Usage and distribution terms
Phi-3.5-mini-instruct is licensed under MIT, while Qwen2.5-Omni-7B 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 Qwen2.5-Omni-7B was released on 2025-03-27.
Qwen2.5-Omni-7B is 7 months newer than Phi-3.5-mini-instruct.
Aug 23, 2024
2.2 years ago
Mar 27, 2025
1.6 years ago
7mo 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 Qwen2.5-Omni-7B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Phi-3.5-mini-instruct vs Qwen2.5-Omni-7B.