Expired50% confidenceTradeoffExact time
Codex's Fast mode employs a parallel inference strategy, simultaneously launching multiple inference threads to handle multiple stages, reducing wait time but multiplying the consumption of computational resources and tokens.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/20/2026
First Seen
Valid until: 10/18/2026(expired)
Sources
Related Claims
UnverifiedSelecting a powerful model in Codex and enabling Fast mode will noticeably accelerate token consumption.77% similarUnverifiedTop-tier models employ techniques such as chain-of-thought or extended reasoning, generating a large number of intermediate tokens during inference, causing per-call token consumption to be several times that of ordinary models.75% similarUnverifiedCodex uses a reasoning model optimized with reinforcement learning and excels at multi-step logical reasoning and code debugging.73% similarUnverifiedCodex的计划模式机制理论基础来自大语言模型领域的思维链推理（Chain-of-Thought Reasoning）73% similarVerifiedSkill encapsulation executes substantial logic through pre-set scripts rather than invoking large model inference each time, guaranteeing output uniqueness and consistency while reducing token costs.70% similar
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