Unverified50% confidenceFactExact time
Comparing on the same 32B model, DeepSeek found that pure RL reached 47% on AIME 2024 while distillation from R1 reached 72.6%, indicating that for small models distillation from a stronger model is more effective than large-scale RL.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/30/2026
First Seen
Valid until: 1/28/2027
Sources
14 Core Concepts of Reasoning Models: From Chain of Thought to GRPO Explained
youtubeBrix AI10/29/2026
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Related Claims
VerifiedDeepSeek R1 offers multiple distilled versions ranging from 1.5B to 671B parameters.74% similarVerifiedDeepSeek's previous R1 model described in its technical report the process of distilling from a self-developed model to smaller-parameter versions.74% similarUnverifiedDeepSeek-R1 distilled models perform strongly on tasks such as AIME 2024, MATH-500, and LiveCodeBench, matching GPT-4o and DeepSeek V3 in most scenarios and surpassing OpenAI o1-mini on some metrics.71% similarUnverifiedThe DeepSeek-R1 32B model is reportedly already capable of achieving very good results.70% similar
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