kimi-k3-in-c alternatives
Curated alternatives to kimi-k3-in-c — and why you'd switch.
colibri
Pure-C, zero-dep MoE runtime that runs GLM-5.2 (744B) on a 25GB-RAM consumer box by streaming experts from disk — VRAM/RAM/NVMe as one tiered hierarchy, never touching precision.
Why switchBoth are pure-C runtimes that stream MoE experts from disk to run frontier models in consumer RAM; colibri targets GLM-5.2 (744B) at usable speed with a VRAM/RAM/NVMe hierarchy, kimi-k3-in-c pushes a 2.78T model into 8 GB, CPU only.
Full comparison →BigMoeOnEdge
Run MoE models bigger than your RAM: keep the always-needed weights resident and stream each token's experts from flash — a 284B model on a 12 GB phone, CPU only, byte-identical output.
Why switchSame insight, resident trunk plus experts streamed from flash with byte-identical output; bigmoeonedge builds on llama.cpp so many models work, kimi-k3-in-c is a from-scratch engine for one model.
Full comparison →airllm
Layer-by-layer inference that runs 70B models on a 4GB GPU — no quantization required; 405B on 8GB, DeepSeek-V3 671B on ~12GB. One AutoModel line for most open model families.
Why switchBoth trade speed for memory to run models far larger than the machine; airllm loads layer by layer on a small GPU, kimi-k3-in-c streams 4-bit experts on CPU alone.
Full comparison →