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 7B Instruct

Alibaba

Qwen2.5 7B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 65.6% across 14 benchmarks. It excels particularly in GSM8k (91.6%), MT-Bench (87.5%), HumanEval (84.8%). The model shows particular specialization in math tasks with an average performance of 83.5%. It supports a 139K token context window for handling large documents. 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 Alibaba's latest advancement in AI technology.

Alibaba

Qwen2.5 7B Instruct

Alibaba

2024-09-19

Microsoft

Phi 4

Microsoft

2024-12-12

2 months newer

Pricing Comparison

Cost per million tokens (USD)

Microsoft

Phi 4

$0.39 cheaper
Input:$0.07
Output:$0.14
Alibaba

Qwen2.5 7B Instruct

Input:$0.30
Output:$0.30

Performance Metrics

Context window and performance specifications

Microsoft

Phi 4

Max Context:32.0K
Parameters:14.7B
Alibaba

Qwen2.5 7B Instruct

Larger context
Max Context:139.3K
Parameters:7.6B

Average performance across 7 common benchmarks

Microsoft

Phi 4

+9.1%
Average Score:67.9%
Alibaba

Qwen2.5 7B Instruct

Average Score:58.9%

Performance comparison across key benchmark categories

Microsoft

Phi 4

math
80.5%
code
+10.2%
76.1%
roleplay
47.6%
general
60.2%
Alibaba

Qwen2.5 7B Instruct

math
+3.0%
83.5%
code
66.0%
roleplay
+14.1%
61.7%
general
+0.4%
60.6%
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 7B Instruct

1 providers

Together

Throughput: 138 tok/s
Latency: 0.5ms
Microsoft

Phi 4

+9.1%
Avg Score:67.9%
Providers:1
Alibaba

Qwen2.5 7B Instruct

Avg Score:58.9%
Providers:1