Supersonic Labs releases Julia 1, a 144.3M-parameter open decision model
Supersonic Labs, a Brazilian AI lab, has released Julia 1, a compact decision model with 144.3M parameters. Unlike standard chatbots, Julia 1 does not generate text; instead, it accepts context, a question, and 2 to 20 candidate answers to select one option and return probability scores. The model is built on JHU CLSP’s mmBERT-small encoder and is available on Hugging Face under the Apache 2.0…
Key points
- Julia 1 is a 144.3M-parameter model released under Apache 2.0 license by Supersonic Labs.
- The model runs on CPUs with a median latency of 33.15 ms on Apple M4 hardware.
- Training cost approximately US$104.08 in cloud GPUs, with a planned API price of $0.025/MTok.
The lab reports that Julia 1 outperformed TypeSafe’s Jev reference values in three of four benchmark pilots, including AG News and DAIR Emotion. However, it significantly underperformed on the Banking77 dataset, scoring 64/100 compared to Jev’s 87/100 reference. Total cloud GPU training costs were approximately US$104.08. On-device latency tests showed a median of 33.15 ms per decision on an Apple M4 chip, while an Intel Core i5-1235U took 107.83 ms for simpler tasks.
Supersonic Labs notes that Julia 1 is limited to comparing supplied options and cannot handle multi-step calculations or missing facts. A hosted API is planned at $0.025 per million tokens but is not yet open. Julia 2, featuring a proprietary foundation architecture, is currently in development.
Model page: Jev →
The story so far
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Supersonic Labs Releases Julia 1: A 144.3M-Parameter Open Decision Model That Runs on a CPU
MarkTechPost · 26 September 2026
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- SupersonicLabs/Julia-1 · Hugging FacePrimary source · huggingface.co ·
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