GPT-5.5 Codex: Is Reasoning-Token Clustering Hurting Performance?
Meta Description: GPT-5.5 Codex reasoning-token clustering may be leading to degraded performance — here's what developers are seeing, why it happens, and how to fix it.
TL;DR: Developers and researchers are reporting that GPT-5.5 Codex's reasoning-token clustering behavior — where the model groups similar reasoning steps into dense token bursts — appears to correlate with measurable drops in output quality, particularly on complex multi-step coding and logic tasks. This article breaks down what's happening, what the evidence shows, and what you can do about it right now.
Key Takeaways
Reasoning-token clustering in GPT-5.5 Codex refers to the model's tendency to batch similar chain-of-thought tokens together rather than distributing them linearly across a reasoning sequence.
