Kimi K3 2.78T Parameter Model Runs on 8GB RAM via Open-Source C Engine

New open-source C engine enables Kimi K3 to run on 8GB RAM using disk streaming and MoE sparse activation, though token generation remains slow at 32.7 seconds.

Woofun AI reports that a developer has released 'kimi-k3-in-c,' an open-source project enabling the 2.78 trillion-parameter Kimi K3 model to operate on devices with only 8GB of memory. The 176KB C99 codebase functions without GPUs, CUDA, PyTorch, or BLAS, relying exclusively on CPU inference. By leveraging Kimi K3's Mixture of Experts architecture, the system activates only 16 of 896 experts per layer, storing most weights on NVMe drives and retrieving them dynamically while streaming dense layers. This configuration requires nearly 1.7TB of high-speed storage and generates one token in approximately 32.7 seconds. The developer characterizes the solution as an experimental infrastructure optimization rather than a practical application tool.