Kimi K3:开放前沿智能
Kimi K3: Open Frontier Intelligence
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中文总结 AI 辅助
介绍Kimi K3这一2.8T参数的专家混合模型,基于Kimi Delta Attention等构建,结合多种方法使缩放效率提升约2.5倍。经训练后在多领域强化学习表现出色,虽整体性能略逊最强专有模型,但在多项任务中达前沿水平且优于其他模型,还发布模型权重助力研究。
中文摘要 AI 辅助
我们介绍了Kimi K3,这是一个拥有2.8T参数的专家混合模型,激活参数达1040亿,具备原生视觉能力和100万个token的上下文窗口。Kimi K3基于Kimi Delta Attention和Attention Residuals构建,与Stable LatentMoE以及优化的训练和数据方法相结合,相比Kimi K2整体缩放效率提高约2.5倍。训练后亮点包括跨多个领域和推理水平的强化学习。在2.8T规模下,它在多方面有基础设施进展。广泛评估表明,Kimi K3在多项任务中达到前沿水平,虽整体性能仍落后于最强大的专有模型,但优于其他模型。我们发布完整模型权重以促进未来研究。
英文摘要
We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is built on Kimi Delta Attention and Attention Residuals, which improve information flow across sequence length and model depth. Together with Stable LatentMoE, which effectively activates 16 of 896 routed experts per token, and refined training and data recipes, these advances yield an approximately 2.5x improvement in overall scaling efficiency over Kimi K2. Post-training highlights reinforcement learning across general, agentic, and coding domains and multiple reasoning-effort levels, enabling compositional generalization and robust long-horizon execution. At 2.8T scale, Kimi K3 is supported by infrastructure advances in multiple areas: algorithm-system co-design for KDA, perfectly balanced expert-parallel training with efficient memory management, million-token agentic RL with persistent rollout and sandbox states, and deployment innovations. Extensive evaluations show that Kimi K3 achieves frontier-level performance across long-horizon coding, agentic, knowledge, reasoning, and vision tasks. While its overall performance still trails the most powerful proprietary models, namely Claude Fable 5 and GPT-5.6 Sol, Kimi K3 consistently outperforms other open and proprietary models evaluated in our suite. We release the full Kimi K3 model weights to facilitate future research and accelerate the broader deployment and adoption of frontier intelligence.