Skip to header Skip to main navigation Skip to main content Skip to footer

OpenAI Puts ChatGPT and Codex on One Token Budget: The Flat-Rate Era Narrows

Breadcrumb

  • Home
  • OpenAI Puts ChatGPT and Codex on One Token Budget: The Flat-Rate Era Narrows
Photograph of OpenAI CEO Sam Altman speaking into a microphone on stage in front of an OpenAI backdrop.

OpenAI is ending the era of separate allowances for chatting and coding. Starting in December, ChatGPT Plus, Pro and Business plans will share a single token budget across ChatGPT and Codex, according to an updated OpenAI support page reported by The Decoder on November 1. The change arrives as OpenAI folds the agentic capabilities of ChatGPT Work into the main ChatGPT interface, a merger the company had already announced.

The mechanics matter more than the announcement. Usage will be measured in tokens, the units a model processes and generates, so more advanced models and more complex tasks will use more of the allowance. Chats with Instant models will not draw from the budget, which keeps quick, casual questions effectively flat-rate. Subscribers will be able to see their combined remaining usage and reset times in Settings, and when the pool runs dry the documented options are to wait for a reset, upgrade, or buy extra credits. OpenAI recently doubled usage limits for its higher-priced plans, apparently in preparation, but it has not published the size of the new shared budgets, an exact December start date, or the price of extra credits. An OpenAI engineer cautioned on October 28 that the merge was not rolling out yet and that the team would proceed carefully, so read the support page as a firm direction of travel, not a finished rollout.

For people who build with these tools, the practical consequence is immediate: a heavy afternoon of Codex agent work will soon compete with every ordinary ChatGPT question for the same allowance. Capacity planning becomes token budgeting. Teams will need to measure their actual burn by model and task, route routine work to Instant or cheaper models where quality allows, and reserve the shared pool for the advanced-model and agent runs that justify it. Anyone treating a subscription as all-you-can-prompt is budgeting on a model that ends in December, and with no published budget sizes, your own measured usage is the only reliable planning input.

The same week brought the mirror image of metering: marking. Anthropic told API customers by email that it is expanding its text watermark to four more models, Claude Mythos 5, Claude Opus 4.7, Claude Opus 4.6 and Claude Sonnet 4.6, with newer models such as Claude Opus 5.5 already carrying it and the Amazon Bedrock rollout possibly taking a few extra days. Anthropic describes the mark as an imperceptible pattern in word choice that changes neither meaning nor price, carries no information about the user, and cannot be switched off. The stated driver is the EU AI Act December deadline: models released after August 2, 2026 shipped with the watermark from day one, and older models are being retrofitted in stages, using a variant of Google DeepMind's SynthID text method, with a detection API in private preview.

There is, however, a documented loophole. On Opus 4.6 and Sonnet 4.6 the watermark applies only when the sampling parameters temperature, top_p and top_k are left at their defaults; changing any one of them is enough to produce unmarked output. Anthropic's own advice is blunt: if you rely on the watermark for your own compliance, keep those settings at their defaults. That caveat captures December's double lesson for builders. Usage is becoming one metered pool, and output is becoming provably labelled, but in both cases the details that decide whether you stay inside the lines are settings and numbers the providers control. Audit yours before December, not after.

Rocky Mountain Madman LLC
OpenAI
Anthropic
Claude
GPT
AI Pricing
AI Policy

Ai Industry News

Anthropic Says One Agent Beats Many: Fold Your Subagents Back Into the Loop

Photograph of Dario Amodei.

Anthropic is telling enterprise builders to do the unfashionable thing: use fewer agents. In guidance published October 22 from its Applied AI team, and reported widely on October 25, the company said that across several enterprise deployments a single agent that loads skills and tools only when needed frequently beat both a one-prompt-for-everything design and a fleet of specialised subagents on quality, and often cost less and ran faster. In one comparison the single-agent setup ran about twice as fast as the multi-agent version it replaced.

  • Read more about Anthropic Says One Agent Beats Many: Fold Your Subagents Back Into the Loop

1Password Lets Agents Log In Without Ever Seeing the Password: The Approval Is the Product

The fastest way to make an AI agent useful is also the fastest way to make it dangerous: give it your passwords. 1Password took direct aim at that bargain on October 22 with 1Password for Agents, a system that lets a supported agent sign in to your accounts without ever seeing, handling, or storing the password itself. Chief executive Aashish Tripathi put the problem plainly in the launch statement: agents are starting to do real work on our behalf, and the old model, where you hand over a credential and hope for the best, does not work.

  • Read more about 1Password Lets Agents Log In Without Ever Seeing the Password: The Approval Is the Product

Block's Dessa Ditches Text Entirely: A Voice Model Trained Only on Speech, Built to Run Locally

Photograph of Jack Dorsey.

Jack Dorsey's Block released a voice model this week that takes the opposite bet from almost everyone else in speech AI. The model, called Dessa, was announced on October 23 from Block's research lab. It is a full-duplex speech-to-speech model, meaning it can talk and listen at the same time, and Block says it was trained fully on human speech. There is no text pipeline in the middle. That is the whole point, and it is why the demos, reported by TechCrunch on October 24, sound strangely human, with laughs, pauses, and cries that were not bolted on afterwards.

  • Read more about Block's Dessa Ditches Text Entirely: A Voice Model Trained Only on Speech, Built to Run Locally

Pagination

  • First page « First
  • Previous page ‹ Previous
  • …
  • Page 4
  • Page 5
  • Page 6
  • Page 7
  • Current page 8
  • Page 9
  • Page 10
  • Page 11
  • Page 12
  • …
  • Next page Next ›
  • Last page Last »

Copyright © 2026 Rocky Mountain Madman LLC - All rights reserved

Developed and Designed by Rocky Mountain Madman LLC