I am a big proponent of using the right tool for a job.
Why?
To be more efficient!
Here's a breakdown of OpenAI models for a task at hand.
🔹 GPT-4o (Omni) – The Multimodal Generalist
This is my default/all-purpose productivity tool with real-time multimodal support.
It handles text, images, audio, and video natively.
It combines the speed of GPT-4 Turbo with vision and voice capabilities.
✅ It's great for:
Summarizing Zoom meetings with shared visuals
Creating reports from mixed formats (PDF + screenshot + notes)
Voice-to-action workflows (e.g., "Summarize this voicemail and draft an email reply")
🔹 GPT-4.5 – The Creative Communicator
It is emotionally intelligent tasks, marketing, and natural-sounding text.
It delivers warmth, clarity, and creativity.
I often adjust my emails with it.
It's good for:
Writing brand stories and product launches
Generating viral copy ideas for social or web
🔹 o4-mini – The Efficient Problem-Solver
It's best for fast, low-cost technical queries in STEM and code.
It can optimize quick, clear answers with minimal tokens.
It's a lightweight model that handles tech support and debugging on the fly.
I have used it for fixing Python errors, pulling metrics from CSV files, and generating stats.
🔹 o4-mini-high – The Precision Specialist
It's good at deep technical accuracy where/when I need to “get it right.”
It has slower inference, but it is much more accurate.
It's ideal for advanced dev work, SQL, and scientific logic.
I have debugged and refactored a lot of advanced SQL code.
It's perfect for writing multi-step SQL queries.
🔹 o3 – The Strategic Analyst
I never used this model but it is best for:
Multi-step reasoning and strategic decision-making.
It handles chain-of-thought and layered planning. (a good prompt can do the same in any model)
Strengths: Excellent for business, risk, and product strategy work.
✅ Great for:
Performing SWOT analysis across multiple markets
Analyzing KPIs over time and suggesting improvements
Simulating go-to-market scenarios
🔹 o1 Pro Mode – The Deep Thinker
Didn't try this model either but it is best for:
Expert-level reasoning and long-form synthesis.
It uses extra compute to “think deeper.”
It is good at producing highly accurate and thoughtful outputs.
✅ Great for:
Writing academic-style papers
Designing economic forecasting models
Performing comparative policy analysis
🎯 Final Thought
Every programming language, database, system setup, or AI model has its strengths and trade-offs. They're built for different jobs. Picking the right one can save you time, money, and a lot of headaches — pick the wrong one, and it’ll cost you more than you think.
Choose smarter!