Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Microsoft

Phi 4 Mini

Microsoft

Phi 4 Mini is a language model developed by Microsoft. It achieves strong performance with an average score of 65.4% across 17 benchmarks. It excels particularly in GSM8k (88.6%), ARC-C (83.7%), BoolQ (81.2%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.

Alibaba

Qwen2.5-Coder 32B Instruct

Alibaba

Qwen2.5-Coder 32B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 64.9% across 15 benchmarks. It excels particularly in HumanEval (92.7%), GSM8k (91.1%), MBPP (90.2%). The model shows particular specialization in reasoning tasks with an average performance of 78.1%. It supports a 256K token context window for handling large documents. The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Alibaba

Qwen2.5-Coder 32B Instruct

Alibaba

2024-09-19

Microsoft

Phi 4 Mini

Microsoft

2025-02-01

4 months newer

Performance Metrics

Context window and performance specifications

Microsoft

Phi 4 Mini

Max Context:-
Parameters:3.8B
Alibaba

Qwen2.5-Coder 32B Instruct

Larger context
Max Context:256.0K
Parameters:32.0B

Average performance across 8 common benchmarks

Microsoft

Phi 4 Mini

Average Score:69.9%
Alibaba

Qwen2.5-Coder 32B Instruct

+0.4%
Average Score:70.3%

Performance comparison across key benchmark categories

Microsoft

Phi 4 Mini

reasoning
73.3%
math
72.2%
factuality
+12.2%
66.4%
general
60.8%
Alibaba

Qwen2.5-Coder 32B Instruct

reasoning
+4.8%
78.1%
math
+2.0%
74.2%
factuality
54.2%
general
+0.7%
61.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Phi 4 Mini

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Microsoft

Phi 4 Mini

0 providers
Alibaba

Qwen2.5-Coder 32B Instruct

4 providers

Hyperbolic

Throughput: 100 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 44 tok/s
Latency: 0.5ms

Fireworks

Throughput: 110 tok/s
Latency: 0.26ms

Lambda

Throughput: 42 tok/s
Latency: 0.5ms
Microsoft

Phi 4 Mini

Avg Score:69.9%
Providers:0
Alibaba

Qwen2.5-Coder 32B Instruct

+0.4%
Avg Score:70.3%
Providers:4