[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-new-method-makes-ai-code-evolution-30-times-cheaper":10,"sections":34},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":29,"feedback":33,"feedback_at":22,"cost_usd":33,"total_tokens":33},10067,"new-method-makes-ai-code-evolution-30-times-cheaper","New Method Makes AI Code Evolution 30 Times Cheaper","FrugalEvo pairs a pricey LLM for strategy with a cheap one for execution, cutting AI code-optimization costs from about $50 to under $2.","Researchers have built an AI system that evolves its own code more efficiently - and a lot more cheaply.\n\nA new paper describes FrugalEvo, a framework for LLM-guided evolutionary programming, the technique that made headlines with AlphaEvolve. Instead of running every step on one expensive model, FrugalEvo splits the labor: a stronger, costlier LLM proposes solution strategies, while a cheaper model writes and refines the actual code. The team also built a cache-efficient harness that reuses shared prompt prefixes across evolution steps to cut redundant computation. Tested on 10 math and systems optimization tasks plus 10 algorithmic tasks from ALE-Bench-Lite, FrugalEvo matched or beat existing baselines including OpenEvolve, ShinkaEvolve, AdaEvolve, and EvoX.\n\nThe headline number is cost. On the classic circle-packing problem, FrugalEvo hit state-of-the-art results for $1.68 using GPT-5.6 Terra and Luna, and for $0.55 using GLM-5.3 and its Flash variant. Multi-agent approaches like CORAL and SwarmResearch needed roughly $50 to reach comparable results - call it a 30x to 90x cost reduction for the same output.\n\nEvolutionary code search has mostly been treated as a brute-force spending contest since AlphaEvolve made headlines; this paper is a reminder that the real constraint was never compute, it was budget discipline.","[\"ai\",\"llm\",\"evolutionary-algorithms\",\"cost-optimization\"]","2026-10-05T04:00:00.000Z","2026-10-05T21:18:44.417Z","2026-10-05T21:18:50.538Z","published",null,[],"ai",[24,26,27,28],"llm","evolutionary-algorithms","cost-optimization",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2610.03675",0,{"sections":35},[36,39,43,48,53,58,62,67,71,76,81,86,91,96],{"name":37,"slug":24,"count":38,"latest_published_at":18},"AI",6293,{"name":40,"slug":41,"count":42,"latest_published_at":18},"Security","security",869,{"name":44,"slug":45,"count":46,"latest_published_at":47},"Policy","policy",444,"2026-10-03T15:02:01.000Z",{"name":49,"slug":50,"count":51,"latest_published_at":52},"Deals","deals",323,"2026-10-04T13:00:00.000Z",{"name":54,"slug":55,"count":56,"latest_published_at":57},"Hardware","hardware",204,"2026-10-03T14:50:50.000Z",{"name":59,"slug":60,"count":61,"latest_published_at":18},"Science","science",178,{"name":63,"slug":64,"count":65,"latest_published_at":66},"Consumer Tech","consumer-tech",158,"2026-10-03T03:21:12.000Z",{"name":68,"slug":69,"count":70,"latest_published_at":18},"Dev Tools","dev-tools",98,{"name":72,"slug":73,"count":74,"latest_published_at":75},"Software","software",97,"2026-10-04T10:00:00.000Z",{"name":77,"slug":78,"count":79,"latest_published_at":80},"Startups","startups",92,"2026-10-04T14:36:25.000Z",{"name":82,"slug":83,"count":84,"latest_published_at":85},"Gaming","gaming",53,"2026-10-02T02:50:39.000Z",{"name":87,"slug":88,"count":89,"latest_published_at":90},"General","general",51,"2026-10-05T02:35:01.000Z",{"name":92,"slug":93,"count":94,"latest_published_at":95},"Reviews","reviews",32,"2026-10-02T18:00:00.000Z",{"name":97,"slug":98,"count":99,"latest_published_at":100},"How-To","how-to",7,"2026-10-01T09:00:00.000Z"]