Echo
Echo is a new experiment that composes multiple open-weight LLMs (e.g., GLM‑5.2, Kimi‑K2.7) dynamically across a shared workload to hit Fable-class results at roughly 1/3 the cost. It automatically routes sub-queries to optimally performant models without locking users into a single-model stack, making it a compelling cost model for R&D orgs and startups looking for competitive inference at lower spend. SaaS product.
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