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@etraut-openai The uploaded thread ID here (019becfa-bd48-7f63-882a-9a90d6052cb9) should be really useful — thanks @nshkrdotcom.This feels like part of the broader “remote compaction can fail hard and strand the session” family (e.g. #9666 is a timeout waiting for the child process; there are a few other remote compact task reports too), just with a different failure mode (context_length_exceeded).
Two thoughts:
If the compaction step itself can hit context_length_exceeded, it likely means the compactor request is still too large (maybe including too much history/tool output). Server-side truncation/chunking of compactor input might help.
UX-wise, if remote compaction fails, a fallback to local compaction (or at least a “continue without compaction” escape hatch) would prevent the user from getting stuck.
If you want to reduce fragmentation, maybe track these under a single canonical “remote compaction failures” issue and link the various thread IDs.
Reacted by nshkrdotcom, Amar Sood, Ignat Remizov and xuiqzy
Same for me. Having PRO plans. So for my case it happened 2 times and maybe seems related to plan mode. Because i was close to full context length and when using Plan mode it made the plan and didnt replay to launch the plan.
Error running remote compact task: { "error": { "message": "Your input exceeds the context window of this model. Please adjust your input and try again.", "type": "invalid_request_error", "param": "input", "code": "context_length_exceeded" } }
I am a 5x Pro package. Can anyone solve this problem for me?
019e4df6-f2ad-7bd3-a8b3-c0b65c4c4565
Reacted by A. M.
Reacted by Index, DhananjayBhosale, 우준혁, Tyomdotcom, weekendjoy and 谷本祥太
Thanks for reporting this problem. Until recently, Codex used a separate endpoint and server-side logic for compaction. We recently switched to a more robust approach where the compaction logic is moved locally using the same endpoint as normal turns. This eliminates "remote compaction" errors and increases the stability and reliability of compaction operations. If you see further problems with compaction, please use /feedback and open a new bug report.
Activity
swordfish444 commentedon Jan 26, 2026
@etraut-openai The uploaded thread ID here (019becfa-bd48-7f63-882a-9a90d6052cb9) should be really useful — thanks @nshkrdotcom.This feels like part of the broader “remote compaction can fail hard and strand the session” family (e.g. #9666 is a timeout waiting for the child process; there are a few other
remote compact taskreports too), just with a different failure mode (context_length_exceeded).Two thoughts:
context_length_exceeded, it likely means the compactor request is still too large (maybe including too much history/tool output). Server-side truncation/chunking of compactor input might help.If you want to reduce fragmentation, maybe track these under a single canonical “remote compaction failures” issue and link the various thread IDs.
nshkrdotcom commentedon Jan 26, 2026
Hasnt happened since, and I have since updated codex.
atomical commentedon Jan 31, 2026
Still experiencing this issue. It may have to do with too much tool output in my case.
Vathivis commentedon Feb 3, 2026
started happening to me as well
id: 019c1eda-5393-7d70-a40c-a93a64ae17d8
Numinex-Corp commentedon Feb 4, 2026
Same for me. Having PRO plans. So for my case it happened 2 times and maybe seems related to plan mode. Because i was close to full context length and when using Plan mode it made the plan and didnt replay to launch the plan.
kcosr commentedon Feb 5, 2026
This has been happening to me for a few days. Previously I was a few versions of Codex behind, but I just upgraded and the problem continues.
019c2b9e-9310-7e43-af8f-ba6a031258db
brianbader commentedon Feb 27, 2026
This has been happening to me as well. I'm running codex on windows using ubuntu wsl.
019c9c8c-8d5e-7d20-96d6-06ddcabcb1d1
edit: the specific error I am seeing is below
bitsydarel commentedon Apr 14, 2026
Error running remote compact task: {
"error": {
"message": "Unknown parameter: 'prompt_cache_retention'.",
"type": "invalid_request_error",
"param": "prompt_cache_retention",
"code": "unknown_parameter"
}
}
SebasGarcia08 commentedon Apr 14, 2026
This is happening to me very often now:
Error running remote compact task: {
"error": {
"message": "Unknown parameter: 'prompt_cache_retention'.",
"type": "invalid_request_error",
"param": "prompt_cache_retention",
"code": "unknown_parameter"
}
}
TheBatashev commentedon Apr 14, 2026
Error running remote compact task: { "error": { "message": "Unknown parameter: 'prompt_cache_retention'.", "type": "invalid_request_error", "param": "prompt_cache_retention", "code": "unknown_parameter" } }
HazelSX2 commentedon Apr 14, 2026
Latest version: very often at pro plan gpt-5.4 highx:
Error running remote compact task: {
"error": {
"message": "Unknown parameter: 'prompt_cache_retention'.",
"type": "invalid_request_error",
"param": "prompt_cache_retention",
"code": "unknown_parameter"
}
}
Running fine again after wait some minutes...
scottweiss commentedon Apr 14, 2026
gpt-5.4 xhigh
■ Error running remote compact task: {
"error": {
"message": "Unknown parameter: 'prompt_cache_retention'.",
"type": "invalid_request_error",
"param": "prompt_cache_retention",
"code": "unknown_parameter"
}
}
temktoznaet commentedon Apr 14, 2026
GPT 5.4
Error running remote compact task: { "error": { "message": "Unknown parameter: 'prompt_cache_retention'.", "type": "invalid_request_error", "param": "prompt_cache_retention", "code": "unknown_parameter" } }
YolozzZ66 commentedon Apr 14, 2026
I wait about 5 mins, and it return running normally.
etraut-openai commentedon Apr 14, 2026
For those who were seeing the "prompt_cache_retention" error, that should be fixed now.
challmy commentedon May 22, 2026
Error running remote compact task: { "error": { "message": "Your input exceeds the context window of this model. Please adjust your input and try again.", "type": "invalid_request_error", "param": "input", "code": "context_length_exceeded" } }

I am a 5x Pro package. Can anyone solve this problem for me?
019e4df6-f2ad-7bd3-a8b3-c0b65c4c4565
etraut-openai commentedon Jun 29, 2026
Thanks for reporting this problem. Until recently, Codex used a separate endpoint and server-side logic for compaction. We recently switched to a more robust approach where the compaction logic is moved locally using the same endpoint as normal turns. This eliminates "remote compaction" errors and increases the stability and reliability of compaction operations. If you see further problems with compaction, please use
/feedbackand open a new bug report.