Agentic Kernel Optimization, visualized.

A swarm of GPT 5.6 Sol agents spent over 40 hours optimizing a Kimi K3-like model from 65 to 406 tok/s.

This animation follows their collaboration as they discover operator fusions, transform the execution graph, and develop new kernel algorithms.

We start with a fully decomposed 331-node Kimi Linear graph and end with a fused version requiring just 22 GPU dispatches per token.

The biggest gains were from custom WebGPU kernels for Kimi Delta Attention (KDA), Multi-Head Latent Attention (MLA), and Mixture of Experts (MoE).

Stay tuned for the full release of this optimization framework.