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Regolo.ai's Brick LLM router optimizes costs by selecting the best model

By PulseAugur Editorial · [1 sources] ·

Regolo.ai has developed Brick, an LLM routing system designed to optimize costs by intelligently selecting the most appropriate model for a given prompt. Unlike traditional cascade systems that involve retries, Brick analyzes a prompt once across six capability dimensions using a ModernBERT classifier and a Qwen3.5-0.8B model to determine complexity. It then selects the most cost-effective model from a user-defined pool that meets the prompt's requirements, aiming to avoid paying premium prices for simpler tasks. AI

IMPACT Enables cost savings for AI deployments by intelligently routing prompts to the most efficient models.

RANK_REASON This is a new software tool for optimizing LLM usage, not a frontier model release or core research.

Read on dev.to — Claude Code tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Regolo.ai's Brick LLM router optimizes costs by selecting the best model

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This is a new software tool for optimizing LLM usage, not a frontier model release or core research.
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COVERAGE [1]

  1. dev.to — Claude Code tag TIER_1 English(EN) · ZyVOP ·

    Brick: The LLM Router That Skips the Cascade and Still Cuts Your Bill

    <p>Most teams solve "which model should answer this prompt" one of two ways.</p> <p>Pick one strong model and pay frontier prices for every request, including the ones a 9B open-weight model could handle blind. Or build a cascade: try the cheap model first, escalate on a low-conf…

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