arXiv:2511.17592v1 Announce Type: cross 
Abstract: Recent advances in LLM-guided evolutionary computation, particularly AlphaEvolve (Novikov et al., 2025; Georgiev et al., 2025), have demonstrated remarkable success in discovering novel mathematical constructions and solving challenging optimization problems. However, the high-level descriptions in published work leave many implementation details unspecified, hindering reproducibility and further research. In this report we present GigaEvo, an extensible open-source framework that enables researchers to study and experiment with hybrid LLM-evolution approaches inspired by AlphaEvolve. Our system provides modular implementations of key components: MAP-Elites quality-diversity algorithms, asynchronous DAG-based evaluation pipelines, LLM-driven mutation operators with insight generation and bidirectional lineage tracking, and flexible multi-island evolutionary strategies. In order to assess reproducibility and validate our implementation we evaluate GigaEvo on challenging problems from the AlphaEvolve paper: Heilbronn triangle placement, circle packing in squares, and high-dimensional kissing numbers. The framework emphasizes modularity, concurrency, and ease of experimentation, enabling rapid prototyping through declarative configuration. We provide detailed descriptions of system architecture, implementation decisions, and experimental methodology to support further research in LLM driven evolutionary methods. The GigaEvo framework and all experimental code are available at https://github.com/AIRI-Institute/gigaevo-core.

تم تقديم GigaEvo كإطار عمل مفتوح المصدر يعتمد على نماذج اللغة الكبيرة (LLMs) والخوارزميات التطورية، مستندًا إلى النجاحات التي حققها AlphaEvolve. يهدف هذا الإطار إلى تعزيز إمكانية التكرار في البحث من خلال توفير تنفيذات معيارية لمكونات مختلفة أساسية لأساليب LLM-التطور الهجينة.

GigaEvo se ha presentado como un marco de optimización de código abierto que aprovecha los modelos de lenguaje de gran tamaño (LLMs) y los algoritmos evolutivos, basándose en los éxitos de AlphaEvolve. Este marco tiene como objetivo mejorar la reproducibilidad en la investigación al proporcionar implementaciones modulares de varios componentes esenciales para enfoques híbridos LLM-evolutivos.

GigaEvo a été présenté comme un cadre d'optimisation open-source qui tire parti des modèles de langage de grande taille (LLMs) et des algorithmes évolutionnaires, s'appuyant sur les succès d'AlphaEvolve. Ce cadre vise à améliorer la reproductibilité dans la recherche en fournissant des mises en œuvre modulaires de divers composants essentiels pour les approches hybrides LLM-évolution.

GigaEvo has been introduced as an open-source optimization framework that leverages large language models (LLMs) and evolutionary algorithms, building on the successes of AlphaEvolve. This framework aims to enhance reproducibility in research by providing modular implementations of various components essential for hybrid LLM-evolution approaches.

GigaEvo: An Open Source Optimization Framework Powered By LLMs And Evolution Algorithms

<img src="https://res.infoq.com/news/2025/12/alphaevolve-google-cloud/en/headerimage/generatedHeaderImage-1765799824535.jpg"/><p>Google Cloud announced the private preview of AlphaEvolve, a Gemini-powered coding agent designed to discover and optimize algorithms for complex engineering and scientific problems. The system is now available through an early access program on Google Cloud, targeting use cases where traditional brute-force or manual optimization methods struggle due to vast search spaces.</p> <i>By Robert Krzaczyński</i>

أعلنت Google Cloud عن المعاينة الخاصة لـ AlphaEvolve، وهو وكيل برمجي مدعوم من Gemini مصمم لاكتشاف وتحسين الخوارزميات لمشاكل الهندسة والعلوم المعقدة. النظام متاح الآن من خلال برنامج الوصول المبكر، مستهدفًا بشكل خاص السيناريوهات التي تكون فيها طرق التحسين التقليدية غير كافية بسبب المساحات الواسعة للبحث.

Google Cloud ha anunciado la vista previa privada de AlphaEvolve, un agente de codificación impulsado por Gemini, diseñado para descubrir y optimizar algoritmos para problemas complejos de ingeniería y científicos. Este sistema ya está disponible a través de un programa de acceso anticipado, dirigido específicamente a escenarios donde los métodos de optimización tradicionales son inadecuados debido a amplios espacios de búsqueda.

Google Cloud a annoncé la prévisualisation privée d'AlphaEvolve, un agent de codage alimenté par Gemini, destiné à découvrir et optimiser des algorithmes pour des défis d'ingénierie et scientifiques complexes. Ce système est désormais disponible via un programme d'accès anticipé, ciblant spécifiquement les scénarios où les méthodes d'optimisation traditionnelles sont inadéquates en raison d'espaces de recherche étendus.

Google Cloud has announced the private preview of AlphaEvolve, a Gemini-powered coding agent aimed at discovering and optimizing algorithms for complex engineering and scientific challenges. This system is now available through an early access program, specifically targeting scenarios where traditional optimization methods are inadequate due to extensive search spaces.

AlphaEvolve Enters Google Cloud as an Agentic System for Algorithm Optimization

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GigaEvo: An Open Source Optimization Framework Powered By LLMs And Evolution Algorithms

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