ChatGPT Models Compared: GPT-5.2, o3 & GPT-5 Mini Guide

OpenAI offers a growing family of ChatGPT models for different needs. This guide covers the current lineup as of February 2026, including GPT-5.2 (Instant, Thinking, and Pro), reasoning models like o3, and budget options like GPT-5 Mini.

Don't have time to read everything? Here's what you need to know:

OpenAI organizes models into two distinct families, each with different strengths:

• GPT series (GPT-5.2, GPT-5 Mini) — General-purpose models that excel across coding, writing, analysis, and conversation
• o-series (o3, o3-pro) — Reasoning-first models that think step-by-step, optimized for math, science, and complex logic

Version History

OpenAI's model lineup has evolved rapidly:

Benchmark Performance

• AIME 2025: 100% (perfect score on mathematical reasoning)
• ARC-AGI-2: 52.9% (abstract reasoning, best in class)
• GPQA Diamond: 92.4% (graduate-level science)
• SWE-Bench Verified: 80.0% (real-world coding, via Codex variant)
• Terminal-Bench 2.0: 64.0% (agentic coding, via Codex variant)

When to Use GPT-5.2

Reasoning Effort Levels

GPT-5.2 Thinking supports configurable reasoning effort via the reasoning_effort parameter:

• low: Quick responses with minimal internal reasoning
• medium: Balanced reasoning for most tasks
• high: Thorough step-by-step reasoning (default)
• xhigh: Maximum reasoning depth (GPT-5.2 Thinking/Pro only). Best for complex coding, math, and expert-level analysis

When to Use GPT-5 Mini

When to Use o3

OpenAI's Codex variants are specialized for autonomous coding workflows. They are fine-tuned from GPT-5.2 with enhanced context handling and tool use for long-running development tasks.

Quality Comparison (Simplified)

OpenAI uses token-based pricing. A token is roughly 4 characters or ¾ of a word.

Cached Input Tokens

OpenAI offers automatic input caching with a 90% discount on cached tokens:

• Automatic: No special API headers required — caching is applied automatically when input prefixes match
• 90% savings: Cached input tokens cost just 10% of the standard input price
• All models: Works across GPT-5.2, o3, and other current models

Cost Optimization Tips

• Use model routing: Send simple queries to GPT-5 Mini, complex ones to GPT-5.2
• Leverage caching: Reuse system prompts for up to 90% input savings
• Adjust reasoning effort: Use lower effort levels when deep reasoning is not needed
• Use Instant over Thinking: For tasks that do not need extended reasoning, use the Instant variant
• Start with Mini: Test if GPT-5 Mini meets your quality needs before upgrading

For users who prefer a subscription over API access, OpenAI offers several ChatGPT plans:

Model IDs

Use these identifiers when calling the OpenAI API:

# Current models (February 2026)
GPT-5.2 Thinking:  gpt-5.2
GPT-5.2 Instant:   gpt-5.2-chat-latest
GPT-5.2 Pro:       gpt-5.2-pro
GPT-5 Mini:        gpt-5-mini
o3:                o3-2025-04-16
GPT-5.3-Codex:     gpt-5.3-codex

Budget options (still available)
GPT-4o-mini:       gpt-4o-mini

Basic API Call (Python)

from openai import OpenAI

client = OpenAI()
Using GPT-5.2 (recommended default)
response = client.chat.completions.create(
model="gpt-5.2",
max_tokens=1024,
messages=[
{"role": "user", "content": "Explain quantum computing"}
]
)
print(response.choices[0].message.content)

Reasoning Effort Control

# Adjust reasoning depth for GPT-5.2 Thinking
response = client.chat.completions.create(
model="gpt-5.2",
max_tokens=16384,
reasoning_effort="xhigh",  # low, medium, high, xhigh
messages=[
{"role": "user", "content": "Prove the Riemann hypothesis..."}
]
)

Model Routing Pattern

def choose_model(task_complexity: str) -> str:
"""Select model based on task complexity."""
models = {
"simple": "gpt-5-mini",           # Fast, cheap
"moderate": "gpt-5.2",            # Balanced (Thinking)
"complex": "gpt-5.2-pro",         # Best quality
"reasoning": "o3-2025-04-16",     # Math/science
"coding": "gpt-5.3-codex"         # Agentic coding
}
return models.get(task_complexity, models["moderate"])

Responses API (GPT-5.2 Pro)

# GPT-5.2 Pro requires the Responses API
response = client.responses.create(
model="gpt-5.2-pro",
input="Analyze the security implications of...",
reasoning={"effort": "xhigh"}
)

Both OpenAI and Anthropic offer frontier models in February 2026. Here's how they compare:

Choosing the right OpenAI model depends on your specific needs:

• Default choice: Start with GPT-5.2 Thinking — it handles most tasks well at a competitive price
• Maximum quality: Upgrade to GPT-5.2 Pro for expert-level analysis and the hardest problems
• Deep reasoning: Use o3 for math, science, and tasks where step-by-step correctness is critical
• Agentic coding: Use GPT-5.3-Codex for autonomous multi-file development workflows
• High volume: Use GPT-5 Mini for chatbots, classification, or cost-sensitive applications

With GPT-5.2, OpenAI has consolidated its model lineup around a single powerful family, retiring older GPT-4o and o4-mini models. The 400K context window, configurable reasoning effort, and competitive pricing make it a strong option for both individual developers and enterprises.