Kimi K3, previewed: inside the first open 3T-class model

Moonshot AI's Kimi K3, announced on July 16, 2026, represents a significant advancement in open-source AI models with its 2.8-trillion parameters, 1-million-token context window, and innovative architecture that surpasses mere scaling. With a focus on scaling efficiency 2.5 times better than its predecessor Kimi K2, Kimi K3 employs four architectural innovations: Kimi Delta Attention (KDA) for linear attention, Gated Multi-head Latent Attention (MLA) for global retrieval, Attention Residuals (AttnRes) for selective depth retrieval, and Stable Latent Mixture of Experts (LatentMoE) for managing a sparse expert pool of 896 experts. These features position K3 at the forefront of current AI trends, as evidenced by its competitive benchmark performance, leading in several areas against other open models while still trailing proprietary systems. The model's detailed mechanics and benchmarks are set to be further explored on Hugging Face upon the release of its weights on July 27, highlighting its expertise in integrating cutting-edge attention mechanisms and efficiently balancing sparsity in model design.

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