Phi 4 vs Qwen2.5 7B Instruct
Phi 4 and Qwen2.5 7B Instruct are closely matched at 4.8 and 1.9 on the LLM Stats Score. Phi 4 is 3.4x cheaper per token.
Microsoft · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Phi 4 and Qwen2.5 7B Instruct are closely matched on the overall LLM Stats Score at 4.8 and 1.9.
In the 7 individual benchmarks reported for both models, Phi 4 wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, Phi 4 is roughly 3.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen2.5 7B Instruct also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Phi 4
- you value its reported benchmark strengths — it wins 5 of 7 exact shared results
- cost matters — it's about 3.4x cheaper per token
- you want the most recent training data — it shipped Dec 2024
Choose Qwen2.5 7B Instruct
- you process long inputs — it offers a 131,072 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for Phi 4 · 14 for Qwen2.5 7B Instruct
Phi 4 outperforms in 5 benchmarks (Arena Hard, GPQA, LiveBench, MATH, MMLU-Pro), while Qwen2.5 7B Instruct is better at 2 benchmarks (HumanEval, IFEval).
Phi 4 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Phi 4 ($0.07/1M tokens) is 4.3x cheaper than Qwen2.5 7B Instruct ($0.30/1M tokens).
For output processing, Phi 4 ($0.14/1M tokens) is 2.1x cheaper than Qwen2.5 7B Instruct ($0.30/1M tokens).
In conclusion, Qwen2.5 7B 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 7.1B more parameters than Qwen2.5 7B Instruct, making it 93.2% larger.
Context Window
Maximum input and output token capacity
Qwen2.5 7B Instruct accepts 131,072 input tokens compared to Phi 4's 16,384 tokens. Phi 4 can generate longer responses up to 16,384 tokens, while Qwen2.5 7B Instruct is limited to 8,192 tokens.
License
Usage and distribution terms
Phi 4 is licensed under MIT, while Qwen2.5 7B 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 Qwen2.5 7B Instruct was released on 2024-09-19.
Phi 4 is 3 months newer than Qwen2.5 7B Instruct.
Dec 12, 2024
1.9 years ago
2mo newerSep 19, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while Qwen2.5 7B 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 Qwen2.5 7B Instruct's cutoff date.
Jun 2024
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Provider Availability
Phi 4 is available from DeepInfra. Qwen2.5 7B Instruct is available from Together.
Phi 4
Qwen2.5 7B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Phi 4 and Qwen2.5 7B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Phi 4 vs Qwen2.5 7B Instruct.