Introducing Kimi k1.5 --- an o1-level multi-modal model
-Sota short-CoT performance, outperforming GPT-4o and Claude Sonnet 3.5 on AIME, MATH-500, LiveCodeBench by a large margin (up to +550%)
-Long-CoT performance matches o1 across multiple modalities (MathVista, AIME, Codeforces, etc)
Full tech report revealed
Key ingredients of k1.5
-Long context scaling. Up to 128k tokens for RL generation. Efficient training with partial rollouts.
-Improved policy optimization: online mirror descent, sampling strategies, length penalty, and others.
-Multi modalities. Joint reasoning over text and vision.
-Sota short-CoT performance, outperforming GPT-4o and Claude Sonnet 3.5 on AIME, MATH-500, LiveCodeBench by a large margin (up to +550%) -Long-CoT performance matches o1 across multiple modalities (MathVista, AIME, Codeforces, etc)
Full tech report revealed
Key ingredients of k1.5 -Long context scaling. Up to 128k tokens for RL generation. Efficient training with partial rollouts. -Improved policy optimization: online mirror descent, sampling strategies, length penalty, and others. -Multi modalities. Joint reasoning over text and vision.