@GPTWare: Uhhhh WTF is this???

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Summary

Colibri runs the 744B parameter GLM-5.2 MoE model on a laptop with 25GB RAM by activating only ~40B parameters per token and streaming experts from disk, all in a single 2,400-line C file with no GPU required.

Uhhhh WTF is this??? 👀👀👀
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Cached at: 07/11/26, 11:23 AM

Uhhhh WTF is this??? 👀👀👀

Zane Chen (@chenzeling4): 744B parameters. On a laptop. With 25GB RAM.

Colibri runs GLM-5.2 (744B MoE) in pure C with zero dependencies. The trick: only ~40B params activate per token, so it keeps the dense part resident and streams experts from disk on demand. A single 2,400-line C file. No GPU, no

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Colibrì is a pure C inference engine that runs the 744B GLM-5.2 MoE model on consumer hardware with ~25GB RAM by streaming experts from disk, achieving ~2.2-2.8 tokens/second with speculative decoding.

@yibie: Recommend this project—a single person wrote an inference engine in pure C, making the 744-billion-parameter GLM-5.2 run on a consumer machine with 25GB RAM. No GPU, no BLAS, no Python runtime—about 1300 lines of C. The core insight is simple: MoE…

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Colibri is an inference engine written in pure C, approximately 1300 lines of code, zero dependencies. It can run the 744-billion-parameter GLM-5.2 MoE model on a consumer machine with 25GB RAM, achieved by streaming loaded routing experts and efficient caching, no GPU or Python runtime needed.

@danveloper: Now everyone does it

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Zane Chen demonstrates Colibri, which runs GLM-5.2 (744B MoE) on a laptop with 25GB RAM using pure C and CPU-only inference, by streaming experts from disk.