Model Comparison
Phi-3.5-mini-instruct vs Qwen2.5-Coder 32B InstructWhich is better in 2026?
Qwen2.5-Coder 32B Instruct significantly outperforms across most benchmarks. Qwen2.5-Coder 32B Instruct is 1.1x cheaper per token.
Verdict: Phi-3.5-mini-instruct vs Qwen2.5-Coder 32B Instruct — which is better?
Phi-3.5-mini-instruct (by Microsoft) and Qwen2.5-Coder 32B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Phi-3.5-mini-instruct outperforms in 2 benchmarks (ARC-C, TruthfulQA), while Qwen2.5-Coder 32B Instruct is better at 8 benchmarks (GSM8k, HellaSwag, HumanEval, MATH, MBPP, MMLU, MMLU-Pro, Winogrande). Qwen2.5-Coder 32B Instruct significantly outperforms across most benchmarks.
On price, Qwen2.5-Coder 32B Instruct is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose Phi-3.5-mini-instruct if…
- you want predictable pricing at $0.10/M input and $0.10/M output
Choose Qwen2.5-Coder 32B Instruct if…
- you want the strongest raw capability — it leads on 8 of 10 shared benchmarks
- cost matters — it's about 1.1x cheaper per token
- you want the most recent training data — it shipped Sep 2024
Performance Benchmarks
Comparative analysis across standard metrics
Phi-3.5-mini-instruct outperforms in 2 benchmarks (ARC-C, TruthfulQA), while Qwen2.5-Coder 32B Instruct is better at 8 benchmarks (GSM8k, HellaSwag, HumanEval, MATH, MBPP, MMLU, MMLU-Pro, Winogrande).
Qwen2.5-Coder 32B Instruct significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Phi-3.5-mini-instruct ($0.10/1M tokens) is 1.1x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, Phi-3.5-mini-instruct ($0.10/1M tokens) is 1.1x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, Phi-3.5-mini-instruct is more expensive than Qwen2.5-Coder 32B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen2.5-Coder 32B Instruct has 28.2B more parameters than Phi-3.5-mini-instruct, making it 742.1% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Both models can generate responses up to 128,000 tokens.
License
Usage and distribution terms
Phi-3.5-mini-instruct is licensed under MIT, while Qwen2.5-Coder 32B 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-3.5-mini-instruct was released on 2024-08-23, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
Qwen2.5-Coder 32B Instruct is 1 month newer than Phi-3.5-mini-instruct.
Aug 23, 2024
1.8 years ago
Sep 19, 2024
1.7 years ago
3w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Phi-3.5-mini-instruct is available from Azure. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
Phi-3.5-mini-instruct
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Key Takeaways
Phi-3.5-mini-instruct
View detailsMicrosoft
Qwen2.5-Coder 32B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about Phi-3.5-mini-instruct vs Qwen2.5-Coder 32B Instruct.