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GPT Codex quality degrades above 180k tokens, users report

By PulseAugur Editorial · [1 sources] ·

Users of OpenAI's GPT Codex are reporting a degradation in quality and reasoning capabilities when processing inputs exceeding approximately 180,000 tokens. This decline in performance manifests as sloppier logic, dropped context, and incorrect assumptions. To mitigate these issues, some users are capping their sessions below this threshold, though this can lead to frequent compaction. AI

IMPACT Highlights practical limitations of current context window sizes for complex coding tasks.

RANK_REASON User discussion about model performance limitations, not a primary release or research finding.

Read on r/OpenAI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GPT Codex quality degrades above 180k tokens, users report

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0 / 100
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Commentary
User discussion about model performance limitations, not a primary release or research finding.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release
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High
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Story freshness
116 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

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COVERAGE [1]

  1. r/OpenAI TIER_2 English(EN) · /u/SnooDonuts4151 ·

    GPT Codex users: at what token count does quality actually degrade for you?

    <!-- SC_OFF --><div class="md"><p>I’ve been using GPT Codex heavily and things start falling apart around 180k tokens. Sloppier reasoning, dropped context, wrong assumptions. I capped my sessions at ~170k, which helps, but now compaction kicks in constantly. Where quality actuall…

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