Verified85% confidenceFactExact time
The o-series models combine chain-of-thought reasoning with reinforcement learning, with the model generating internal thinking steps before producing an answer.
5
Sources
85%
Confidence
Long-term
Relevance
7/11/2026
First Seen
Sources
GPT-5.6三模型解析：Sol/Terra/Luna定价与监管困局
bilibili63号炼金工坊7/1/2026
Related Claims
VerifiedThe reasoning paradigm is essentially the application of reinforcement learning to the post-training stage of language models, allowing the model to autonomously explore reasoning paths and receive reward feedback based on answer correctness, first publicly demonstrated in the o1 series of models.84% similarVerifiedOpenAI's o1 series models internalize Chain of Thought as a core mechanism of model training, using reinforcement learning to teach the model to automatically unfold detailed reasoning processes.82% similarVerifiedOpenAI's o-series reasoning models introduce a slow-thinking mechanism that performs internal chain-of-thought reasoning before outputting the final answer.80% similarUnverifiedo1、DeepSeek-R1等模型将思维链内化为训练目标，在输出答案前生成大量内部草稿推理79% similarVerified推理能力基于思维链（Chain-of-Thought, CoT）技术，模型在给出最终答案前生成内部逐步推导过程79% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/488004API
curl https://kongchang.com/api/v1/knowledge/claims/488004MCP
get_claim(id=488004)