Reasoning Model Output Parsing With Thinking Extraction

via “thinking-models-and-extended-reasoning-support”

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Unique: Thinking token handling is integrated into the inference pipeline, not a post-processing step. KV cache management accounts for thinking token overhead, preventing OOM errors when reasoning tokens exceed output tokens by orders of magnitude.

vs others: More transparent than OpenAI's o1 API because thinking tokens are accessible for debugging; more flexible than vLLM because it supports arbitrary thinking token formats without requiring model-specific parsing