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-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

Microsoft

2024-12-12

2 months newer

Pricing Comparison

Cost per million tokens (USD)

Microsoft

Phi 4

Input:$0.07
Output:$0.14
Alibaba

Qwen2.5-Coder 32B Instruct

$0.03 cheaper
Input:$0.09
Output:$0.09

Performance Metrics

Context window and performance specifications

Microsoft

Phi 4

Max Context:32.0K
Parameters:14.7B
Alibaba

Qwen2.5-Coder 32B Instruct

Larger context
Max Context:256.0K
Parameters:32.0B

Average performance across 4 common benchmarks

Microsoft

Phi 4

+10.7%
Average Score:79.5%
Alibaba

Qwen2.5-Coder 32B Instruct

Average Score:68.8%

Performance comparison across key benchmark categories

Microsoft

Phi 4

math
+6.3%
80.5%
code
+18.0%
76.1%
general
60.2%
Alibaba

Qwen2.5-Coder 32B Instruct

math
74.2%
code
58.2%
general
+1.3%
61.5%
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-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

+10.7%
Avg Score:79.5%
Providers:1
Alibaba

Qwen2.5-Coder 32B Instruct

Avg Score:68.8%
Providers:4