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OpenAI Codex

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The autonomous software engineering agent that writes, tests, and ships code — in parallel

94

Overall score

43

Heat score

Pricing

ChatGPT Plus$20/month
ChatGPT Pro$200/month
ChatGPT Business$30/user/month
ChatGPT EnterpriseCustom — contact sales
API — codex-mini-latest$1.50/M input tokens — $6.00/M output tokens — 75% prompt caching discount
API — GPT-5.2-Codex$1.25/M input tokens — $10.00/M output tokens

Technical Specs

Inputs

Natural Language Task Description, GitHub Repository, Codebase Context, AGENTS.md Instructions, Bug Report, Feature Spec, Pull Request, Screenshot, CI Pipeline Log

Outputs

Written Code, Edited Files, Pull Request, Bug Fix, Test Suite, Codebase Explanation, Documentation, Refactored Code, Pipeline Autofix, Implementation Plan

AI Type

Agentic AI

Model Architecture

GPT-style Decoder

Daily Prompts

N/A

Context Length

N/A

Output Quality

Accuracy

95%

Content

93%

Reasoning

96%

Company Profile

Company

OpenAI

Founded

2015

HQ

San Francisco, California, USA

Employees

3.5K

Total Raised / Total Funding

$11.3B

Revenue

$3.7B

Valuation

$157B

ARR

N/A

CEO

Sam Altman

Overview

Estimated Paid Users

1M

Current estimate

Total Earnings Till Date

N/A

No monthly delta yet

Market Share

8.4%

Current share

Average Session

90

Per active user

Hallucination Rate

5%

Model quality signal

Growth Rate

N/A

Monthly active users

Burn Rate

N/A

Total expenses / years active

Paid User Gain

N/A

Monthly paid user trend

No demo video available yet.

Platforms

AD

Performance Metrics

Accuracy

95%

Context

93%

Reasoning

96%

Safety

90%

Benchmarks

No benchmark scores available.

OpenAI Codex Models

No model/version data available.

Funding Rounds & Investors

Total Funding

$11.3B

Rounds

0

No funding rounds available.

Founders/Team

TS

Thibault Sottiaux

Head of Codex — OpenAI

WZ

Wojciech Zaremba

Co-Founder & Original Codex Lead — OpenAI

MC

Mark Chen

Chief Research Officer & Early Codex Researcher — OpenAI

Direct competitors

No direct competitors available.

Change Log / Major Updates

No changelog entries available.

Compliance, Integrations & Support

Industry: Software Development

Compliances: Not specified

Integrations: GitHub, VS Code, Codex CLI, OpenAI Responses API, OpenAI Agents SDK, MCP Protocol, ChatGPT, Azure OpenAI, Codex Autofix CI

Support:email, help center, developer docs, enterprise support, community forum

Target audience: Software Engineers, Senior Developers, Engineering Teams, DevOps Engineers, Enterprise Engineering Organizations, Open Source Maintainers, CTOs, AI Builders, Platform Engineers

Supported languages: English, Python, JavaScript, TypeScript, Java, C++, C#, Go, Rust, Ruby, PHP, Swift, Kotlin, Shell, SQL, HTML, CSS, YAML, JSON, Terraform

OpenAI Codex Acquisitions

No acquisition records available.

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Reviews & Rating

0 reviews

No reviews yet

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0.0

Accuracy

0.0

Ease of Use

0.0

Output Quality

0.0

Security

0.0

Social Feed

No social feed available for this tool yet.

More About OpenAI Codex

In the fall of 2024, OpenAI leadership declared building an autonomous software engineer the company's top-line goal for 2025. The directive came from the top: Sam Altman and Greg Brockman believed OpenAI itself should have an AI working alongside every engineering team, not as a suggestion engine, but as an independent contributor capable of receiving a task, working on it for up to 30 minutes in an isolated sandbox, and opening a pull request when done. The result, launched May 16, 2025, was Codex — powered by codex-1, a version of the o3 reasoning model fine-tuned on real-world software engineering tasks using reinforcement learning, optimized to generate code that mirrors human style and pull request preferences.

The adoption curve was unlike anything OpenAI had seen for a developer product. Usage grew 5x between January and February 2026. A million developers now use it every week. The Codex desktop app, launched February 2026, was described by Sam Altman as "the most loved internal product we've ever had." What distinguishes Codex from interactive coding assistants like Copilot or Cursor is its asynchronous, multi-agent architecture: where those tools wait for you to prompt them, Codex works independently. You describe ten tasks in the morning — fix this bug, refactor that module, write tests for this function, answer why this test is failing — and Codex dispatches parallel cloud agents to each one simultaneously, working in separate sandboxed environments with preloaded copies of your repository. OpenAI engineers use it for exactly this: triaging on-call issues, offloading repetitive tasks like renaming and refactoring, writing tests, and planning tasks at the start of the day so they can focus on architecture while Codex handles execution. The "30/70 rule" has emerged inside OpenAI: some engineers now spend 30% of their time directing agents and 70% reviewing their output — an inversion of the traditional coding ratio that points toward where software engineering is going. By February 2026, Codex writes 90%+ of its own application code — making it one of the first production software systems substantially building itself.

OpenAI Codex FAQ's

No FAQs available.