VQV Signal
According to a post on X by @Tim_Hua_, the same GLM-5.3 model shows different chain-of-thought reasoning when run inside Claude Code's harness than when run inside Codex's harness. The post is mainly side-by-side screenshots and was reshared by @minsik_nlp. Its point is that the scaffold, or harness, around a model can shape how that model reasons. The source snippet gives no further measurements or formal evaluation.
According to a post on X by @Tim_Hua_, the same GLM-5.3 model shows different chain-of-thought reasoning when run inside Claude Code's harness than when run inside Codex's harness. The post is mainly side-by-side screenshots and was reshared by @minsik_nlp. Its point is that the scaffold, or harness, around a model can shape how that model reasons. The source snippet gives no further measurements or formal evaluation.
AI-assisted summary based on the listed source.
@Tim_Hua_ posted side-by-side screenshots of GLM-5.3's chain of thought when the same model runs inside the Claude Code harness versus the Codex harness. It's mainly images, a reminder that the scaffold shapes how a model reasons, and was reshared by @minsik_nlp. Also:...
Developers comparing coding agents may find that the same underlying model behaves differently depending on the wrapper it runs in. Teams choosing tools should consider the harness as a variable alongside the model itself. Watch for a fuller write-up or test results showing whether these reasoning differences affect the code the model produces.
VQV organizes public signals from inspectable sources. It does not independently verify the underlying report.
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
VQV surfaced this signal because it is recent, relevant to AI Coding Tools, connected to Scobleizer News Pulse (X).
No login, cookies, social SDKs, or automatic posting.
