OpenAI has expanded access to the 1-million-token context window for GPT-5.6 Sol in Codex to users with ChatGPT accounts, according to an announcement from OpenAI engineer Tibo Sottiaux. The change makes the larger context setting available beyond API access, although the maximum context supported by the model should not be confused with the amount automatically used in every Codex session. OpenAI’s API documentation lists a 1.05-million-token context window for GPT-5.6 Sol, while the default settings in Codex have been subject to separate limits and configuration choices. The update gives users the option to work with more code, tool output and conversation history in a single session when the larger setting is available. It also comes with a practical consideration: larger contexts can use more tokens, meaning users may reach applicable usage limits sooner.
GPT-5.6 Sol’s Larger Context Becomes Available To ChatGPT Users
The change concerns GPT-5.6 Sol, OpenAI’s model for complex reasoning and coding. OpenAI’s official model documentation lists a 1.05-million-token context window for the model, along with a maximum output of 128,000 tokens. The update was announced by OpenAI engineer Tibo Sottiaux on X. His post said the 1-million-token context option, which had previously been available through API access, had been enabled for ChatGPT accounts using Codex.
A context window determines how much information a model can have available during a task. In Codex, that can include source code, previous conversation history and output from tools used during a coding session. A larger window can allow more of that material to remain available before older information needs to be compacted or summarized. For developers, the distinction can matter when working on larger repositories or extended tasks. Instead of repeatedly reducing the amount of previous information available to the model, a larger context can provide more room for files, instructions and tool results to remain part of the active session. Sottiaux described the default context size as a balance between performance and cost, with users able to opt into the larger setting when a task calls for it.
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That distinction has also been discussed by Codex users. Reddit discussions from July and August show users comparing different context limits for GPT-5.6 Sol, with some reporting effective windows below the model’s published 1.05-million-token API specification.
Why Codex Users Report Different Context Limits
The gap between the model’s published maximum and the context actually available in a given Codex configuration has been a recurring subject among users. An issue in OpenAI’s public Codex repository reported that the Codex desktop app was giving GPT-5.6 Sol an effective context window of about 353,400 tokens despite the API documentation listing 1.05 million.
Other reports have described different limits across Codex interfaces. Another GitHub issue reported that interactive Codex sessions showed a 1.05-million-token window while codex exec sessions showed about 258,000 tokens for the same model. They show that the product’s effective context settings have changed or differed across configurations. There is also a usage consideration. OpenAI’s API documentation says requests above 272,000 input tokens for GPT-5.6 Sol are priced at higher rates, while Sottiaux has described the default context as a performance-and-cost tradeoff.
Codex users have separately reported concerns about larger contexts consuming their available usage more quickly. Some Reddit users have recommended keeping a lower context setting for ordinary tasks and using larger windows when a project actually requires them.
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For users working with large codebases, the option could be useful when keeping more project information available is important. For shorter coding tasks, however, the larger setting may not provide the same practical benefit. The update ultimately gives ChatGPT users another context-size option for GPT-5.6 Sol in Codex. Its practical effect will depend on which Codex interface and account configuration a user has, how much context a task requires and how the larger window affects their available usage.
