Physix Frontier · News Briefing Card (enbrief · Oct 5, 2026)

StartLux Open-Sources Five-Tier Decision Model, Beats Jev on 31 of 38 Benchmarks

KEY FACTS

On September 30, Shanghai-based AI company StartLux released StartLux-Decision, an open-source decision model.
The model launched in five parameter versions at once: 0.8B, 2B, 4B, 9B, and 27B.
The team used an Auto Research method to complete development and validation in 3 days.
The 27B version scored 63.88 on Decision Index 0.2.1, beating Jev 1.13 on 31 of 38 benchmarks.
The 27B version averaged 91.82% accuracy across seven evaluations, higher than Jev's 88.74%.

KEY DATA

63.8827B decision composite score

57.91Jev 1.13 decision composite score

91.82%27B average accuracy across seven evaluations

26ms4B average latency for short requests

PHYSIX OBSERVATION

The decision model race is shifting from parameter count to interface efficiency. StartLux uses 3-day iteration and five tiers to lower the barrier to local deployment, and its approach of completing multiple judgments in a single request is more valuable for agent deployment than topping leaderboards. But self-reported data diverges from official certification, so developers should choose based on their own tasks.

Source: enbrief original report ↗