Model Comparison

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

Microsoft

Phi 4

Microsoft

Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model shows particular specialization in math tasks with an average performance of 80.5%. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Alibaba

Qwen2.5 VL 32B Instruct

Alibaba

Qwen2.5 VL 32B Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 63.6% across 28 benchmarks. It excels particularly in DocVQA (94.8%), Android Control Low_EM (93.3%), HumanEval (91.5%). The model shows particular specialization in code tasks with an average performance of 87.8%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Microsoft

Phi 4

Microsoft

2024-12-12

Alibaba

Qwen2.5 VL 32B Instruct

Alibaba

2025-02-28

2 months newer

Performance Metrics

Context window and performance specifications

Microsoft

Phi 4

Larger context
Max Context:32.0K
Parameters:14.7B
Alibaba

Qwen2.5 VL 32B Instruct

Max Context:-
Parameters:33.5B

Average performance across 5 common benchmarks

Microsoft

Phi 4

+1.5%
Average Score:74.9%
Alibaba

Qwen2.5 VL 32B Instruct

Average Score:73.4%

Performance comparison across key benchmark categories

Microsoft

Phi 4

code
76.1%
math
+15.4%
80.5%
general
+0.1%
60.2%
Alibaba

Qwen2.5 VL 32B Instruct

code
+11.6%
87.8%
math
65.1%
general
60.1%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Phi 4

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

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
Alibaba

Qwen2.5 VL 32B Instruct

0 providers
Microsoft

Phi 4

+1.5%
Avg Score:74.9%
Providers:1
Alibaba

Qwen2.5 VL 32B Instruct

Avg Score:73.4%
Providers:0