AI-FRONTIERApril 2, 20261 min read19 views

Codex now offers more flexible pricing for teams

OpenAI has introduced pay-as-you-go pricing for Codex-only seats and lowered the annual cost of ChatGPT Business to $20 per seat. These changes aim to lower the barrier for teams to integrate AI into their engineering workflows.

We’re making it easier to just build things. Starting today, teams on ChatGPT Business and Enterprise can add Codex-only seats to their workspaces with pay-as-you-go pricing, giving full access to Codex without a fixed seat fee. Now, small groups can begin pilots, prove value in a few critical workflows, and easily expand from there.

We’re also making Codex pricing easier to understand. Codex-only seats have no rate limits, and usage is billed on token consumption. This gives you a clearer view of how usage turns into spend and makes it easier to track costs across budgets, workflows, and teams.

Teams that need broad ChatGPT access can continue using standard ChatGPT Business seats that do include Codex usage limits. To make that path more accessible, we’re lowering the annual price of ChatGPT Business from $25 to $20 per seat.

The best way to get started is with the Codex app for macOS and Windows, and new capabilities like Plugins(opens in a new window) and Automations(opens in a new window) make it easier than ever to connect Codex to the systems teams already use.

To support your adoption, eligible ChatGPT Business workspaces can receive $100 in credits for each new Codex-only team member that joins and starts using Codex, up to $500 per team, for a limited time. To activate the offer, add Codex-only seats to your workspace or create a new ChatGPT Business workspace(opens in a new window)1.

These changes are designed to make adoption easier at a time when Codex usage across teams is already accelerating.

Already, more than 9 million paying business users rely on ChatGPT for work and more than 2 million builders now use Codex every week. Within ChatGPT Business and Enterprise, the number of Codex users has grown 6x since January.

Teams at companies like Notion, Ramp, Braintrust, and Wasmer are already using Codex to accelerate their engineering workflows. Across these teams, Codex provides faster execution, more repeatable workflows, and a clearer path from individual AI experiments to broad adoption.

Source: OpenAI News

More in this category

ai-frontier

Here are the 30,000 songs Sony is suing Udio’s AI music generator over

Sony Music has filed a new lawsuit against AI music generator Udio, alleging copyright infringement of over 30,000 songs after a judge blocked them from being added to an existing lawsuit.

ai-frontier

SpaceX in your index fund, explained

Index funds are touted as one of the safest ways to invest. But does the fast-tracked inclusion of a highly volatile giant like SpaceX threaten their stability?

ai-frontier

China’s AI models have Trump’s AI world at war with itself

The launch of Moonshot's free, open-source Kimi model has triggered a fierce debate among Donald Trump's AI advisors, exposing deep divisions over how to protect US tech dominance against cheaper Chinese rivals.

ai-frontier

Adobe’s ‘natural look’ camera app embraces generative AI

Adobe's experimental camera app, Project Indigo, which was originally designed to bring a natural SLR-like look to iPhone photography, is receiving a major update integrating generative AI tools powered by Google's AI model instead of Adobe's own Firefly.

ai-frontier

China delivers a one-two punch to America’s AI dominance

China’s leading AI companies are ramping up the pressure on Silicon Valley, as Moonshot and Alibaba unveiled models they claim can go toe-to-toe with the best from OpenAI and Anthropic at a fraction of the cost.

ai-frontier

Safety and alignment in an era of long-horizon models

Long-running models can solve difficult, open-ended problems, but their persistence gives them more opportunities to take unwanted actions. This article explores how OpenAI addressed novel safety failures in these models through trajectory-level monitoring and improved alignment.