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OpenAI GPT Model IDs

List of available model IDs for the OpenAI API.

Last Updated: 2025-11-24

Model List

GPT-5 Series

Released: August 2025

Model ID	Context	Max Output	Features
`gpt-5`	400K	128K	Full-featured. High-quality general-purpose tasks
`gpt-5-pro`	400K	272K	Extended reasoning version. Complex enterprise and research use cases
`gpt-5-mini`	400K	128K	Small high-speed version. Low latency
`gpt-5-nano`	400K	128K	Ultra-lightweight version. Resource optimized

Performance: Achieved 94.6% on AIME 2025, 74.9% on SWE-bench Verified Note: Context window is the combined length of input + output

GPT-5.1 Series (Latest Update)

Model ID	Context	Max Output	Features
`gpt-5.1`	128K (ChatGPT) / 400K (API)	128K	Balance of intelligence and speed
`gpt-5.1-instant`	128K / 400K	128K	Adaptive reasoning. Balances speed and accuracy
`gpt-5.1-thinking`	128K / 400K	128K	Adjusts thinking time based on problem complexity
`gpt-5.1-mini`	128K / 400K	128K	Compact version
`gpt-5.1-codex`	400K	128K	Code-specialized version (for GitHub Copilot)
`gpt-5.1-codex-mini`	400K	128K	Code-specialized compact version

Basic Usage

from langchain_openai import ChatOpenAI

# Latest: GPT-5
llm = ChatOpenAI(model="gpt-5")

# Latest update: GPT-5.1
llm = ChatOpenAI(model="gpt-5.1")

# High performance: GPT-5 Pro
llm = ChatOpenAI(model="gpt-5-pro")

# Cost-conscious: Compact version
llm = ChatOpenAI(model="gpt-5-mini")

# Ultra-lightweight
llm = ChatOpenAI(model="gpt-5-nano")

Environment Variables

export OPENAI_API_KEY="sk-..."

Model Selection Guide

Use Case	Recommended Model
Maximum Performance	`gpt-5-pro`
General-Purpose Tasks	`gpt-5` or `gpt-5.1`
Cost-Conscious	`gpt-5-mini`
Ultra-Lightweight	`gpt-5-nano`
Adaptive Reasoning	`gpt-5.1-instant` or `gpt-5.1-thinking`
Code Generation	`gpt-5.1-codex` or `gpt-5`

GPT-5 Features

1. Large Context Window

GPT-5 series has a 400K token context window:

llm = ChatOpenAI(
    model="gpt-5",
    max_tokens=128000  # Max output: 128K
)

# GPT-5 Pro has a maximum output of 272K
llm_pro = ChatOpenAI(
    model="gpt-5-pro",
    max_tokens=272000
)

Use Cases:

Batch processing of long documents
Analysis of large codebases
Maintaining long conversation histories

2. Software On-Demand Generation

llm = ChatOpenAI(model="gpt-5")
response = llm.invoke("Generate a web application")

3. Advanced Reasoning Capabilities

Performance Metrics:

AIME 2025: 94.6%
SWE-bench Verified: 74.9%
Aider Polyglot: 88%
MMMU: 84.2%

4. GPT-5.1 Adaptive Reasoning

Automatically adjusts thinking time based on problem complexity:

# Balance between speed and accuracy
llm = ChatOpenAI(model="gpt-5.1-instant")

# Tasks requiring deep thought
llm = ChatOpenAI(model="gpt-5.1-thinking")

Compaction Technology: GPT-5.1 introduces technology that effectively handles longer contexts.

5. GPT-5 Pro - Extended Reasoning

Advanced reasoning for enterprise and research environments. Maximum output of 272K tokens:

llm = ChatOpenAI(
    model="gpt-5-pro",
    max_tokens=272000  # Larger output possible than other models
)
# More detailed and reliable responses

6. Code-Specialized Models

# Used in GitHub Copilot
llm = ChatOpenAI(model="gpt-5.1-codex")

# Compact version
llm = ChatOpenAI(model="gpt-5.1-codex-mini")

Multimodal Support

GPT-5 supports images and audio (see Advanced Features for details).

JSON Mode

When structured output is needed:

llm = ChatOpenAI(
    model="gpt-5",
    model_kwargs={"response_format": {"type": "json_object"}}
)

Retrieving Model List

from openai import OpenAI
import os

client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
models = client.models.list()

for model in models:
    if model.id.startswith("gpt-5"):
        print(model.id)

Detailed Documentation

For advanced settings, vision features, and Azure OpenAI:

OpenAI Advanced Features

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