Jin’s Daily AI Trivia: Which OpenAI Model Is This?

Today, OpenAI unveiled another “O-series” model—right on the heels of yesterday’s announcement of base model GPT‑4.1 (4.1, 4.1‑mini, and 4.1‑nano). The new lineup now includes:

• o3
• o3‑pro (coming soon)
• o4‑mini‑high
• o4‑mini

Confused by all these names? Let me break down the evolution of the GPT and O-series models for you:

GPT‑2 (2019)

• OpenAI’s first public release (1.5 B parameters).

GPT‑3 (2021)

• Sparked the AI hype.
• Davinci model: 175 B parameters.
• Underpins the original ChatGPT.

GPT‑3.5 (2022)

• Introduced the turbo variant and basic browsing.
• Marked the start of OpenAI’s subscription model.

GPT‑4 (2023)

• Estimated at 1.76 T parameters.
• First multimodal model (text + image inputs).
• Free ChatGPT users access GPT‑4‑turbo (text-only).

GPT‑4o (2024)

• “O” stands for “omni.”
• Real-time text, image, and audio input/output.
• Free users on image/audio get GPT‑4o‑mini; Plus users use GPT‑4o‑mini as their base.

GPT‑4o Imagen (March 2025)

• Native image generation—an alternative to DALL·E 3.
• Powers the new “Ghibli-style” image output.

GPT‑4.5 (2025)

• OpenAI’s largest, most expensive model yet.
• Available only to Plus and Pro subscribers.

GPT‑4.1 (2025)

• A leaner, more cost-effective spin‑down of GPT‑4.5.
• Replaces GPT‑4o in the lineup.

OpenAI‑o1 (2024)

• First “thinking” model with the “O” prefix. O-series.
• o1‑pro is the priciest AI model, at $150/600 USD per million tokens.

OpenAI‑o3 (2025)

• A leaner, more cost-effective spin‑down of o1.
• o3‑mini launched in January 2025 for Plus users.
• “o2” was skipped due to trademark issues.
• Full o3‑pro model to follow later this year.

OpenAI‑o4 (2025)

• Released alongside o3 today.
• Currently available only as o4‑mini and o4‑mini‑high.
• Includes basic image-transform tools (crop/rotate) for better analysis.
• Rumor has it OpenAI rushed to launch o4 to compete with Gemini 2.5 Pro and Qwen. (not even bigger model)

Initial Benchmarking:

o4‑mini behind Gemini 2.5 Pro by a slim margin—but it’s significantly cheaper, especially for large-token contexts. If you need robust multimodal performance on a budget, o4‑mini is your go‑to.