Phi-4 vs GPT-4o-mini Face-Off

When LLMs first arrived, they impressed the world with their scale and capabilities. But then came their sleeker, more efficient cousins—small language models (SLMs). Compact, nimble, and surprisingly powerful, SLMs are proving that bigger isn’t always better. As we head into 2025, the focus is squarely on unlocking the potential of these smaller, smarter models. Leading the charge are Phi-4 and GPT-4o-mini. Both the models have their pros and cons. To test out which one of them is actually better for day-to-day tasks, I have tested them on 4 tasks. Let’s see Phi-4 vs GPT-4o-mini performance below!

Phi-4 vs GPT-4o-mini: An Overview

Phi-4, developed by Microsoft Research, focuses on reasoning-driven tasks using synthetic data generated through innovative methodologies. This approach boosts STEM-related capabilities and optimizes training efficiency for reasoning-heavy benchmarks​.

GPT-4o-mini represents OpenAI’s pinnacle in multimodal LLMs. It incorporates Reinforcement Learning from Human Feedback (RLHF) to refine performance on diverse tasks, achieving top scores in exams like the Uniform Bar Exam and excelling in multilingual benchmarks​.

Phi-4 vs GPT-4o-mini: Core Architectures and Training Methodologies

Phi-4: Optimized for Reasoning

It builds upon the foundations of the Phi family, employing a decoder-only transformer architecture with 14 billion parameters. Unlike its predecessors, Phi-4 places heavy emphasis on synthetic data, leveraging diverse techniques such as multi-agent prompting, self-revision, and instruction reversal to generate datasets tailored for reasoning and problem-solving. The model’s training employs a carefully curated curriculum, focusing on quality rather than sheer scale, and integrates a novel approach to Direct Preference Optimization (DPO) for refining outputs during post-training​.

Key architectural features of Phi-4 include:

• Synthetic Data Dominance: A significant portion of training data comes from synthetic sources, meticulously curated to enhance reasoning depth and problem-solving skills.
• Extended Context Length: Training starts with a context length of 4K, extended to 16K during mid-training, allowing improved handling of long-form inputs​.

GPT-4o-mini: Multimodal and Scalable

GPT-4o-mini represents a step forward in OpenAI’s GPT series, designed as a Transformer-based model pre-trained on a mix of publicly available and licensed data. A distinguishing feature of GPT-4o-mini is its multimodal capability, which allows the processing of text and image inputs to generate text outputs. OpenAI’s predictable scaling approach ensures consistent optimization across varying model sizes, supported by a robust infrastructure​.

Distinctive traits of GPT-4o-mini include:

• Reinforcement Learning from Human Feedback (RLHF): Fine-tuning via RLHF significantly enhances factuality and alignment with user intents.
• Scaling Predictability: Methodologies such as loss prediction and performance extrapolation ensure optimized training outcomes across model iterations

To know more visit OpenAI.

Phi-4 vs GPT-4o-mini: Performance on Benchmarks

Phi-4: Specialization in Reasoning and STEM

It demonstrates exceptional performance in reasoning-heavy benchmarks, often surpassing models of similar or larger sizes. Its emphasis on synthetic data generation tailored for STEM and logical tasks has led to remarkable outcomes:

• GPQA (Graduate-level STEM Q&A): Phi-4 significantly outperforms gpt-4o-mini-mini, achieving a score of 56.1 compared to gpt-4o-mini’s 40.9​.
• MATH Benchmark: With a score of 80.4, Phi-4 excels in mathematical problem-solving, showcasing its training focus on structured reasoning​.
• Contamination-Proof Testing: By using benchmarks like the November 2024 AMC-10/12 math tests, Phi-4 validates its ability to generalize without overfitting​.

GPT-4o-mini: Broad Excellence Across Domains

GPT-4o-mini shines in versatility, performing at human levels across a variety of professional and academic tests:

• Exams: GPT-4o-mini exhibits human-level performance on the majority of professional and academic exams

• MMLU (Massive Multitask Language Understanding): gpt-4o-mini outperforms previous language models across diverse subjects, including non-English languages​.

Phi-4 vs GPT-4o-mini: Comparative Insights

While Phi-4 specializes in STEM and reasoning tasks, leveraging synthetic datasets for enhanced performance, GPT-4o-mini exhibits a balanced skill set across traditional benchmarks, excelling in multilingual capabilities and professional exams. This distinction underscores the divergent philosophies of the two models—one focused on domain-specific mastery, the other on generalist proficiency.

Code Implementation of Phi-4 vs GPT-4o-mini

Phi-4

# Install the necessary libraries

!pip install transformers

!pip install torch

!pip install huggingface_hub

!pip install accelerate

from huggingface_hub import login

from IPython.display import Markdown

# Log in using your Hugging Face token (copy your token from Hugging Face account)

login(token="your_token")

import transformers

# Load the Phi-4 model for text generation

phi_pipeline = transformers.pipeline(

   "text-generation",

   model="microsoft/phi-4",

   model_kwargs={"torch_dtype": "auto"},

   device_map="auto",

)

messages = [

   {"role": "system", "content": "You are a data scientist providing insights and explanations to a curious audience."},

   {"role": "user", "content": "How should I explain machine learning to someone new to the field?"}

]

GPT-4o mini

!pip install openai

from getpass import getpass

OPENAI_KEY = getpass('Enter Open AI API Key: ')

import openai

from IPython.display import HTML, Markdown, display

openai.api_key = OPENAI_KEY

def get_completion(prompt, model="gpt-4o-mini"):

   messages = [{"role": "user", "content": prompt}]

   response = openai.chat.completions.create(

       model=model,

       messages=messages,

       temperature=0.0, # degree of randomness of the model's output

   )

   return response.choices[0].message.content

response = get_completion(prompt= '''You are a data scientist providing insights and explanations to a curious audience.How should I explain machine learning to someone new to the field?''',

                         model='gpt-4o-mini')

display(Markdown(response))

Task 1: Reasoning Performance Comparison

Prompt:

• Observation: The sun has risen in the east every day for the past 1,000 days.
• Question: Will the sun rise in the east tomorrow? Why?

Phi-4 Code

messages = [{"role": "user", "content": '''Observation: The sun has risen in the east every day for the past 1,000 days.

Question: Will the sun rise in the east tomorrow? Why?

'''}]

# Generate output based on the messages

outputs = phi_pipeline(messages, max_new_tokens=256)

# Print the generated response

Markdown(outputs[0]['generated_text'][1]['content'])

Phi-4 Output

GPT-4o-mini Code

response = get_completion(prompt= '''Observation: The sun has risen in the east every day for the past 1,000 days.

Question: Will the sun rise in the east tomorrow? Why?''',model='gpt-4o-mini')

display(Markdown(response))

GPT-4o-mini Output

Analysis of Both Outputs:

1. Tone: GPT-4-mini adopts a philosophical and reflective tone, emphasizing the limitations of scientific certainty and considering broader implications. In contrast, Phi-4 is straightforward and factual, focusing on delivering clear and precise explanations without venturing into philosophical territory.
2. Structure: GPT-4-mini presents its argument in a single compact paragraph, combining scientific explanation with reflective insights. On the other hand, Phi-4 organizes its content into multiple paragraphs, ensuring a logical and systematic progression of ideas.
3. Clarity: While GPT-4-mini’s explanation is concise, its inclusion of philosophical elements may make it feel abstract to some readers. Phi-4, however, prioritizes clarity and is easier to follow due to its structured breakdown of facts.
4. Depth: GPT-4-mini delves into the philosophical underpinnings of scientific reasoning, discussing the assumptions behind natural laws. Phi-4 focuses more on empirical details, such as Earth’s rotational direction and the stability of natural phenomena over time.
5. Scientific Reasoning: Both discuss the same scientific principle—Earth’s rotation causing the sun to rise in the east—but GPT-4-mini frames this within the context of philosophical inquiry, while Phi-4 emphasizes the consistency of the pattern and the improbability of disruption.
6. Likelihood of Event: GPT-4-mini acknowledges that the prediction of the sun rising tomorrow is highly reliable yet not an absolute certainty. Phi-4 explicitly states the high likelihood, supported by historical and natural stability, without delving into epistemological concerns.
7. Audience Suitability: GPT-4-mini appeals to readers seeking intellectual depth and reflection, whereas Phi-4 is more suitable for readers who prioritize clear, factual, and direct explanations.

Verdict

Both outputs are well-crafted but serve different purposes. If your goal is to engage readers who value philosophical insight and are interested in exploring the limitations of scientific certainty, GPT-4-mini is the better choice. However, if the objective is to deliver a clear, factual, and direct explanation rooted in empirical reasoning, Phi-4 is the more suitable option.

For general educational purposes or scientific communication, Phi-4 is stronger due to its clarity and structured explanation. On the other hand, GPT-4-mini is ideal for discussions involving critical thinking or addressing audiences inclined towards conceptual and reflective inquiry.

Overall, Phi-4 wins in accessibility and precision, while GPT-4-mini stands out in depth and nuance. The choice depends on the context and the target audience.

Task 2: Coding Performance Comparison

Prompt:   

Implement a function to calculate the nth Fibonacci number using dynamic programming.

Phi-4

GPT-4o-mini

Analysis of Both Outputs:

1. Introduction and Explanation:
   • Phi-4: Provides a clear, concise explanation of using dynamic programming for Fibonacci calculation. The introduction briefly explains the iterative approach without much elaboration on why it’s efficient compared to other methods.
   • GPT-4-mini: Offers a more detailed introduction, explicitly discussing the Fibonacci sequence’s definition and why dynamic programming is preferable due to its efficiency over the naive recursive approach.
2. Error Handling:
   • Phi-4: Implements error handling for negative indices, raising a ValueError with the message “Fibonacci numbers are not defined for negative indices.”
   • GPT-4-mini: Uses a similar approach but refines the error message to “Input should be a non-negative integer.” This phrasing is broader and more precise.
3. Code Style:
   • Phi-4: Uses straightforward comments to guide the reader, keeping the explanations minimal and to the point.
   • GPT-4-mini: Includes slightly more descriptive comments, aiming to ensure clarity for less experienced readers (e.g., describing the purpose of array creation more explicitly).
4. Structure and Logic:
   • Both outputs use the same logic for Fibonacci calculation with an iterative bottom-up approach, initializing the first two Fibonacci numbers and iterating to fill the array. The implementation is virtually identical.
5. Output Example:
   • Phi-4: Provides an example at the end using n = 10, outputting the 10th Fibonacci number.
   • GPT-4-mini: Also includes an example with the same format, making the usage identical.
6. Tone:
   • Phi-4: Maintains a more formal tone, focusing on direct explanation and implementation.
   • GPT-4-mini: Adopts a slightly more conversational and instructional tone, making it more engaging for learners.
7. Audience:
   • Phi-4: Suitable for readers who are already familiar with dynamic programming and need a quick, clear implementation.
   • GPT-4-mini: Targets a broader audience, including beginners, by providing additional context and a more comprehensive explanation.

Verdict:

Both outputs are excellent implementations of the Fibonacci sequence using dynamic programming. Phi-4 is better suited for a technically experienced audience that values concise explanations, while GPT-4-mini is more appropriate for learners or those who appreciate detailed guidance and contextual information.

Task 3: Creativity Performance Comparison

Prompt: Write a short children’s story

Phi-4

GPT-4o-mini

Analysis of Both Outputs:

1. Story Theme:
   • Phi-4 (“The Magic Garden”): The story is whimsical and fantastical, set in a magical garden where kindness and dreams come to life. It focuses on the emotional and mystical experience of Lily discovering and cherishing the magical garden.
   • GPT-4-mini (“The Great Cookie Caper”): The story is lighthearted and humorous, revolving around a mystery and teamwork to resolve it. It focuses on Benny and Lucy’s cooperation to bake cookies and highlights friendship as its central theme.
2. Setting:
   • Phi-4: Set in a mystical, idyllic location—a garden hidden in nature that feels timeless and magical. The setting conveys serenity and wonder.
   • GPT-4-mini: Set in a lively town, Sweetville, during a festive event. The setting is vibrant and energetic, centered around a community celebration.
3. Characterization:
   • Phi-4: Focuses on a single protagonist, Lily, whose purity of heart allows her to access the magical world. A friendly squirrel briefly appears as a guide.
   • GPT-4-mini: Features two main characters, Benny the Bunny and Lucy the Squirrel, with a stronger emphasis on their dynamic. Benny is determined and Lucy is playful but apologetic.
4. Plot Development:
   • Phi-4: The plot is simple and linear—Lily discovers the garden, interacts briefly with its magic, and leaves with a transformed heart. The focus is on exploration and personal growth.
   • GPT-4-mini: The plot is more dynamic, involving a problem (missing cookie dough), a lighthearted confrontation, and a resolution through teamwork. The narrative has a clearer conflict and resolution structure.
5. Tone:
   • Phi-4: The tone is calm, dreamy, and reflective, evoking wonder and enchantment.
   • GPT-4-mini: The tone is cheerful, playful, and humorous, aiming to entertain with a sense of fun.

Verdict:

Both stories excel in their respective styles. Phi-4 creates an enchanting and moral-focused tale suitable for those drawn to fantasy and reflection, while GPT-4-mini delivers a lively and humorous narrative with a clear problem-solving arc, making it more engaging for readers seeking entertainment and fun. The choice depends on whether the audience prefers magical wonder or playful adventure.

Task 4: Summarization Performance Comparison

Prompt: summarize the following text 

Johannes Gutenberg (1398 – 1468) was a German goldsmith and publisher who introduced printing to Europe. His introduction of mechanical movable type printing to Europe started the Printing Revolution and is widely regarded as the most important event of the modern period. It played a key role in the scientific revolution and laid the basis for the modern knowledge-based economy and the spread of learning to the masses. Gutenberg many contributions to printing are: the invention of a process for mass-producing movable type, the use of oil-based ink for printing books, adjustable molds, and the use of a wooden printing press. His truly epochal invention was the combination of these elements into a practical system that allowed the mass production of printed books and was economically viable for printers and readers alike. In Renaissance Europe, the arrival of mechanical movable type printing introduced the era of mass communication which permanently altered the structure of society. The relatively unrestricted circulation of information—including revolutionary ideas—transcended borders, and captured the masses in the Reformation. The sharp increase in literacy broke the monopoly of the literate elite on education and learning and bolstered the emerging middle class.

Phi-4

GPT-4o-mini

Analysis of Both Outputs:

1. Clarity and Conciseness:
   • Phi-4: The summary is well-structured and clear, providing a systematic breakdown of Gutenberg’s contributions and their societal impact. It maintains a professional tone with detailed explanations.
   • GPT-4-mini: The summary is also clear and concise but slightly more compact, combining information into longer sentences and paragraphs, which can feel denser.
2. Tone:
   • Phi-4: Adopts a more descriptive and academic tone, suitable for readers who prefer a formal style with structured detail.
   • GPT-4-mini: While still formal, it has a slightly more flowing and narrative tone, which may feel more engaging to some readers.
3. Focus on Key Contributions:
   • Phi-4: Highlights Gutenberg’s key inventions (movable type, oil-based ink, adjustable molds, and the wooden press) as part of a systematic process, emphasizing the practicality and economic viability of the system.
   • GPT-4-mini: Also lists Gutenberg’s innovations but focuses slightly more on their transformative societal effects, such as fostering a knowledge-based economy and increasing literacy.
4. Impact on Society:
   • Phi-4: Discusses the societal impacts, including the rise of mass communication, breaking the monopoly of the literate elite, and supporting the middle class, but in a more segmented and step-by-step way.
   • GPT-4-mini: Tends to merge these societal impacts into a cohesive narrative, emphasizing how the spread of revolutionary ideas transformed society as a whole.
5. Historical Context:
   • Phi-4: Places significant emphasis on the Renaissance and how Gutenberg’s inventions aligned with the era of mass communication, highlighting the broader historical importance.
   • GPT-4-mini: Mentions the Renaissance but integrates it within the context of societal and intellectual transformation, tying it closely to revolutionary ideas and education.
6. Readability:
   • Phi-4: Easier to digest for readers seeking a step-by-step breakdown of Gutenberg’s contributions and their effects.
   • GPT-4-mini: More engaging for readers looking for a cohesive and flowing narrative that connects historical facts with their broader implications.

Verdict:

Both summaries are accurate and effective but differ in style and emphasis:

• Phi-4 is better suited for readers who prefer a clear, detailed, and structured academic approach.
• GPT-4-mini is ideal for readers who prefer a narrative-driven summary with a stronger focus on the societal transformations caused by Gutenberg’s innovations.

The choice depends on the audience’s preference for structure versus narrative flow.

Result

Conclusion

Phi-4 excels in STEM and reasoning tasks through synthetic data and precision, while GPT-4o-mini shines in versatility, multimodal capabilities, and human-like performance. It suits technical audiences needing to be structured, logic-driven outputs, whereas GPT-4o-mini appeals to broader audiences with creativity and generalist proficiency. Phi-4 prioritizes specialization and clarity, while GPT-4o-mini emphasizes flexibility and engagement. The choice depends on whether depth or breadth is required for the task or audience.

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Pankaj Singh

Hi, I am Pankaj Singh Negi - Senior Content Editor | Passionate about storytelling and crafting compelling narratives that transform ideas into impactful content. I love reading about technology revolutionizing our lifestyle.