Model Guide

Model‑Intro Matrix

Model	Core strength	Ideal first reach‑for	Watch‑outs	Escalate / Downgrade path
GPT‑4o	Real‑time voice / vision chat	Live multimodal agents	Slightly below 4.1 on text SOTA (state-of-the-art)	Need deep reasoning → o4‑mini
GPT‑4.1	1 M‑token text accuracy king	Long‑doc analytics, code review	Cannot natively reason; higher cost than minis	Tight budget → 4.1‑mini / nano
o3	Deep tool‑using agent	High‑stakes, multi‑step reasoning	Latency & price	Cost/latency → o4‑mini
o4‑mini	Cheap, fast reasoning	High‑volume “good‑enough” logic	Depth ceiling vs o3	Accuracy critical → o3

(Full price and utility table → Section 6.1)

Model Evolution at a Glance

OpenAI’s model lineup has evolved to address specialized needs across different dimensions. These diagrams showcase the current model families and their relationships.

Fundamental Differences: “o-series” vs “GPT” Models

OpenAI offers two distinct model families, each with unique strengths:

• GPT Models (4o, 4.1): Optimized for general-purpose tasks with excellent instruction following. GPT-4.1 excels with long contexts (1M tokens) while GPT-4o has variants for realtime speech, text-to-speech, and speech-to-text. GPT-4.1 also comes in a mini, and nano variant, while GPT-4o has a mini variant. These variants are cheaper and faster than their full-size counterparts.

• o-series Models (o3, o4-mini): Specialized for deep reasoning and step-by-step problem solving. These models excel at complex, multi-stage tasks requiring logical thinking and tool use. Choose these when accuracy and reasoning depth are paramount. These models also have an optional reasoning_effort parameter (that can be set to low, medium, or high), which allows users to control the amount of tokens used for reasoning.

OpenAI Model Evolution

Key Characteristics

• GPT-4.1 Family: Optimized for long context processing with 1M token context window.

• o3: Specialized for deep multi-step reasoning.

• o4-mini: Combines reasoning capabilities with vision at lower cost.

Each model excels in different scenarios, with complementary strengths that can be combined for complex workflows.