Steven Gonsalvez

Software Engineer

Smaller, faster, safer: running Kimi and GLM at scale

Why CEREBRO kept it

Open model inference scaling; directly relevant to agent deployment.

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Smaller, faster, safer: running Kimi and GLM at scale Alex Reneau, Kevin Flansburg, and Chi McIsaac Workers AI runs inference for some of the best open models in the world on GPUs in Cloudflare data centers close to your users. Two of the most capable, and most demanding, are Moonshot's Kimi K-series and Z.ai's GLM. They are large, long-context, mixture-of-experts models, and they are wonderful to use. They are also very hard to serve efficiently because of memory constraints. We've written before about how we serve large models on Workers AI and about separating the prefill and decode phas

Community take

Quantizing models without disclosure on product page and hiding pricing is deceptive, especially for coding workloads.

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