Model Comparison

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

OpenAI

GPT-4.1 mini

OpenAI

GPT-4.1 mini is a multimodal language model developed by OpenAI. The model shows competitive results across 29 benchmarks. It excels particularly in CharXiv-D (88.4%), MMLU (87.5%), IFEval (84.1%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.

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.

Microsoft

Phi 4

Microsoft

2024-12-12

OpenAI

GPT-4.1 mini

OpenAI

2025-04-14

4 months newer

Pricing Comparison

Cost per million tokens (USD)

OpenAI

GPT-4.1 mini

Input:$0.40
Output:$1.60
Microsoft

Phi 4

$1.79 cheaper
Input:$0.07
Output:$0.14

Performance Metrics

Context window and performance specifications

OpenAI

GPT-4.1 mini

Larger context
Max Context:1.1M
Microsoft

Phi 4

Max Context:32.0K
Parameters:14.7B

Average performance across 3 common benchmarks

OpenAI

GPT-4.1 mini

+10.9%
Average Score:78.9%
Microsoft

Phi 4

Average Score:68.0%

Performance comparison across key benchmark categories

OpenAI

GPT-4.1 mini

code
+8.0%
84.1%
math
73.1%
general
45.9%
Microsoft

Phi 4

code
76.1%
math
+7.4%
80.5%
general
+14.3%
60.2%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-4.1 mini

2024-05-31

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

OpenAI

GPT-4.1 mini

2 providers

ZeroEval

Throughput: 150 tok/s
Latency: 5ms

OpenAI

Throughput: 150 tok/s
Latency: 5ms
Microsoft

Phi 4

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
OpenAI

GPT-4.1 mini

+10.9%
Avg Score:78.9%
Providers:2
Microsoft

Phi 4

Avg Score:68.0%
Providers:1