codex - 💡(How to fix) Fix GPT-5.5 needs opt-in 1M context in Codex Desktop; the current 258K effective limit is breaking long-running development workflows [2 comments, 3 participants]

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openai/codex#20761Fetched 2026-05-03 04:46:02
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Please prioritize shipping opt-in 1M-token context for GPT-5.5 in Codex Desktop.

This is not a cosmetic request, and it is not simply that "more context would be nice." The current effective limit in Codex Desktop is materially reducing the reliability of long-running engineering workflows. In practice, GPT-5.5 sessions begin recurring memory compaction around the current ~258K effective input budget, and those compactions are lossy enough to degrade complex tasks.

OpenAI has already acknowledged that GPT-5.5 supports 1M context at the model/API level, while Codex currently exposes a much smaller product limit. I understand capacity planning is required, and I am not asking for 1M to become the default for everyone. I am asking for an explicit opt-in path for power users, even if it consumes usage at a higher rate.

Root Cause

model_context_window = 1000000 is not a viable workaround for GPT-5.5 today because the Codex model catalog caps GPT-5.5 at a 272K max context window, so local overrides are clamped or ignored. This differs from GPT-5.4, where Codex previously allowed a 1M max context option.

Fix Action

Fix / Workaround

model_context_window = 1000000 is not a viable workaround for GPT-5.5 today because the Codex model catalog caps GPT-5.5 at a 272K max context window, so local overrides are clamped or ignored. This differs from GPT-5.4, where Codex previously allowed a 1M max context option.

RAW_BUFFERClick to expand / collapse

Summary

Please prioritize shipping opt-in 1M-token context for GPT-5.5 in Codex Desktop.

This is not a cosmetic request, and it is not simply that "more context would be nice." The current effective limit in Codex Desktop is materially reducing the reliability of long-running engineering workflows. In practice, GPT-5.5 sessions begin recurring memory compaction around the current ~258K effective input budget, and those compactions are lossy enough to degrade complex tasks.

OpenAI has already acknowledged that GPT-5.5 supports 1M context at the model/API level, while Codex currently exposes a much smaller product limit. I understand capacity planning is required, and I am not asking for 1M to become the default for everyone. I am asking for an explicit opt-in path for power users, even if it consumes usage at a higher rate.

Why this is urgent

For real development work, the current limit is not enough for:

  • multi-hour debugging sessions where exact failed attempts, logs, stack traces, environment constraints, and hypotheses need to remain available;
  • large architectural refactors where the working plan itself becomes substantial and must remain stable across many tool calls;
  • codebases with large AGENTS.md / project rules, generated plans, design docs, and multiple relevant source files;
  • cross-module changes where the model must preserve invariants across many files and not rediscover them after every compaction;
  • repeated build / test / fix loops where command quirks, prior errors, and partial fixes are critical context rather than disposable chat history.

When compaction runs repeatedly, the model often loses exact details that were necessary for later steps. The visible effect is not just inconvenience. It causes:

  • re-reading and re-discovering the same repository facts;
  • repeated failed commands and repeated debugging branches;
  • drift from the original task objective after compaction;
  • lower completion rate for complex tasks;
  • more tokens and credits spent recovering state instead of progressing;
  • user intervention to restate context that the tool previously had.

This directly harms developer productivity and makes GPT-5.5 feel worse suited for large tasks than it should be, even though the model itself is stronger.

Current behavior

Codex Desktop currently exposes an effective GPT-5.5 context around ~258K input tokens. This appears to come from the Codex product limit of 400K total context, with 272K input and 128K reserved output, plus the harness's effective usable budget.

model_context_window = 1000000 is not a viable workaround for GPT-5.5 today because the Codex model catalog caps GPT-5.5 at a 272K max context window, so local overrides are clamped or ignored. This differs from GPT-5.4, where Codex previously allowed a 1M max context option.

Request

Please ship one of the following as soon as possible:

  1. an official model_context_window = 1000000 path for GPT-5.5 in Codex Desktop;
  2. a tiered opt-in, e.g. 512K / 768K / 1M;
  3. a UI-level advanced setting in Codex Desktop that makes the tradeoff explicit;
  4. a higher usage multiplier for long-context GPT-5.5 if needed for capacity / cost reasons.

Keeping 400K as the default is completely reasonable. Hard-blocking power users from opting into the model's full long-context capability is not.

Expected behavior

A Pro / Business / Enterprise user should be able to opt into GPT-5.5 long context in Codex Desktop and verify the active input budget in /status or the status UI. Compaction should not repeatedly interrupt long-running tasks at ~258K when the user has explicitly selected a larger context window.

Related context

I am filing this separately to emphasize the practical product impact: the current context limit is already causing avoidable compaction churn and reducing task completion quality in real development workflows. Please treat this as a high-priority Codex Desktop reliability and productivity issue, not a minor enhancement.

extent analysis

TL;DR

Increase the context limit for GPT-5.5 in Codex Desktop to 1M tokens through an opt-in mechanism to improve reliability and productivity for power users.

Guidance

  • Review the current Codex product limit and harness's effective usable budget to understand the root cause of the 258K input token limit.
  • Consider implementing a tiered opt-in system, such as 512K / 768K / 1M, to allow power users to choose their desired context window.
  • Evaluate the feasibility of adding a UI-level advanced setting in Codex Desktop to make the tradeoff between context window size and usage multiplier explicit.
  • Investigate the possibility of increasing the usage multiplier for long-context GPT-5.5 sessions to accommodate capacity and cost concerns.

Example

No code snippet is provided as the issue is related to product configuration and limits rather than code implementation.

Notes

The current limit is causing significant issues with compaction churn and task completion quality, and increasing the context limit is crucial for improving the reliability and productivity of Codex Desktop for power users.

Recommendation

Apply a workaround by implementing an opt-in mechanism for power users to increase the context limit to 1M tokens, as this will directly address the current limitations and improve the overall user experience.

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FAQ

Expected behavior

A Pro / Business / Enterprise user should be able to opt into GPT-5.5 long context in Codex Desktop and verify the active input budget in /status or the status UI. Compaction should not repeatedly interrupt long-running tasks at ~258K when the user has explicitly selected a larger context window.

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codex - 💡(How to fix) Fix GPT-5.5 needs opt-in 1M context in Codex Desktop; the current 258K effective limit is breaking long-running development workflows [2 comments, 3 participants]