Expired50% confidenceFactExact time
The performance of the O1 model can be continuously improved along two dimensions: train-time compute and inference-time compute.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 9/30/2026(expired)
Sources
Andrew Ng's New Course Explained: A Practical Guide to Using OpenAI's O1 Reasoning Model
bilibili吴恩达智能体6/13/2026
Related Claims
VerifiedInference-time scaling improves model performance by increasing computation during the inference phase, and exhibits a power-law relationship similar to that of pre-training.76% similarUnverifiedThe core mechanism of the o1 series models is inference-time compute scaling, which performs deep reasoning by generating a long chain-of-thought process during the inference phase.76% similarVerifiedTest-time Compute Scaling improves model performance by investing more computational resources during the inference stage, and research indicates it is more efficient than simply increasing model parameter count on certain tasks.74% similar
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