macOS CLI/App: gpt-5.5 reports 950k context but fails around 260k input
What version of Codex CLI is running?
Terminal CLI: codex-cli 0.141.0
Codex app bundled CLI: codex-cli 0.142.0-alpha.1
Codex app version: 26.616.32156
What subscription do you have?
Pro
Which model were you using?
gpt-5.5, reasoning effort xhigh
What platform is your computer?
macOS 26.5 (25F71), Apple Silicon / arm64
What issue are you seeing?
Both Codex CLI-origin sessions and Codex app/Desktop-origin sessions are becoming unrecoverable with:
Codex ran out of room in the model's context window. Start a new thread or clear earlier history before retrying.
The suspicious part is that the active model metadata reports a 950k effective context window, but the session fails when an individual turn reaches roughly the old 258k-264k active input range.
Current local model metadata:
{
"slug": "gpt-5.5",
"context_window": 1000000,
"max_context_window": 1000000,
"effective_context_window_percent": 95,
"effective_input_budget": 950000
}
I verified this from both the terminal CLI and the app-bundled CLI.
Local evidence
CLI-origin failure
Thread id: 019ee16d-dcdd-74c2-b695-ebb84c28b728
Last token-count events before the failure:
timestamp model_context_window last_input_tokens cumulative_input_tokens cumulative_total_tokens
2026-06-19T20:25:47.589Z 950000 259628 9095382 9134877
2026-06-19T20:26:00.225Z 950000 263127 9358509 9398884
2026-06-19T20:26:09.437Z 950000 264113 9622622 9663574
2026-06-19T20:26:12.355Z 950000 264113 9622622 9663574
2026-06-19T20:26:12.358Z 950000 0 0 950000
The log DB records a codex_core::session::turn turn error for that thread at 2026-06-19 20:26:12 with the context-window error.
Codex app/Desktop-origin failure
Thread id: 019edca6-fe7d-7d90-a366-685b13a74419
Last token-count events before the failure:
timestamp model_context_window last_input_tokens cumulative_input_tokens cumulative_total_tokens
2026-06-18T23:04:10.358Z 950000 223393 5825605 5849870
2026-06-18T23:04:23.405Z 950000 227859 6053464 6078348
2026-06-18T23:04:39.783Z 950000 259390 6312854 6338392
2026-06-18T23:04:40.351Z 950000 259390 6312854 6338392
2026-06-18T23:04:40.353Z 950000 0 0 950000
The log DB records a codex_core::session::turn turn error for that thread at 2026-06-18 23:04:40 with the same context-window error.
Why this looks like a bug
This does not look like a stale local catalog at process start. Both currently installed CLI paths report gpt-5.5 as 1,000,000 context / 950,000 effective input.
It looks more like one of these:
- the visible/session metadata path reports 950k, but a backend or remote-compaction path still enforces the old ~258k effective limit;
- remote compaction is not triggering early enough before that old boundary;
- or the turn is reset/null-completed after a failed compaction/context guard.
Related reports
This seems closely related to:
- https://github.com/openai/codex/issues/29080 (
950k context but compacts/fails around 260k-270k) - https://github.com/openai/codex/issues/29039 (
Context window changes from 1M to 258K mid-thread) - https://github.com/openai/codex/issues/28937 (exact app error on macOS)
- https://github.com/openai/codex/issues/23643 (context fills unusually fast / unrecoverable long sessions)
What steps can reproduce the bug?
I do not have a minimal deterministic reproduction yet. In practice it occurs during reasonably long gpt-5.5 xhigh sessions through both CLI and Codex app/Desktop. The failure appears when the last active turn input reaches roughly 259k-264k, despite model_context_window reporting 950000.
What is the expected behavior?
If the active session reports a 950k effective context window, it should not become unrecoverable around 260k active input. Codex should either:
- honor the 950k effective budget consistently across request, compaction, and backend paths; or
- display the true active enforced budget; and
- compact safely before the hard limit, without leaving the thread in a null/finished unrecoverable state.
Additional information
I can provide more local log snippets or upload feedback for the affected thread IDs if that is useful.
This issue has 1 comment on GitHub. Read the full discussion on GitHub ↗