10ms Decision Intelligence: Running Julia-1 on Apple Metal with Coni's Native CSP Engine

Wed, 07 Oct 2026 18:00:00 +0900

A week ago, I wrote about how Coni’s native CSP meets Ollama 0.35’s System One API. The premise was simple: traditional generative LLMs are excruciatingly slow when all you need is a routing decision. By replacing token-by-token autoregressive generation with single-token classification models (like nimble), we achieved instant decision-making and orchestrated massive agent swarms using Coni’s Go-backed Goroutines (spawn) and channels (chan).

And then, SupersonicLabs dropped Julia-1.

Julia-1 is not just another decision model. It is an architectural leap forward: a 144-million parameter bidirectional decision model based on ModernBERT (mmBERT-small). Instead of forcing causal left-to-right attention onto a classification task, Julia-1 evaluates entire prompts bidirectionally with specialized marker tokens, pre-norm transformer heads, and learned type embeddings.

Julia-1 on NicoLabs

10ms Decision Intelligence: Running Julia-1 on Apple Metal with Coni's Native CSP Engine