[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-cut-ai-training-cost-in-half-with-smarter-distillation":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},3152,"cut-ai-training-cost-in-half-with-smarter-distillation","Cut AI Training Cost in Half With Smarter Distillation","New research shows training small models on just half a sequence's tokens preserves 91% of math benchmark performance while halving memory and compute costs.","Researchers found you can slash AI training costs by 50% without gutting the results.\n\nThe study targets a common workflow: taking a large, expensive reasoning model and distilling its capabilities into a smaller, cheaper student model. That process normally means training on long sequences of data split into three parts — the prompt, the chain-of-thought reasoning steps, and the final answer. The researchers found that training on only the chain-of-thought portion is effective when that section already encodes the prompt and answer information, and that sequences have a length ceiling beyond which adding more tokens yields almost nothing. Cutting every training sequence to its first 50% of tokens preserved an average of roughly 91% of full-sequence performance on math benchmarks.\n\nThe compute savings are concrete: roughly 50% reductions each in training time, memory usage, and floating-point operations. For teams running distillation pipelines at scale, that is a meaningful cost difference — not a rounding error.\n\nSmaller models that can reason well are a recurring priority in AI research right now, and efficiency techniques like this one are often where the real competitive advantage lives, well away from the headline model releases that dominate the news cycle. The code is public on GitHub, so anyone can test the protocol — which is about as close as research gets to putting its money where its abstract is.","[\"ai\",\"machine-learning\",\"model-distillation\",\"research\"]","2026-07-01T04:00:00.000Z","2026-07-01T08:31:53.307Z","2026-07-01T08:31:56.149Z","published",null,[],"ai",[24,26,27,28],"machine-learning","model-distillation","research",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2512.21002",0,{"sections":35},[36,40,45,50,55,60,65,70,75,80,85,89,94,99],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",294,"2026-07-15T19:59:48.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":64},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":66,"slug":67,"count":68,"latest_published_at":69},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":71,"slug":72,"count":73,"latest_published_at":74},"Science","science",66,"2026-07-10T10:29:37.000Z",{"name":76,"slug":77,"count":78,"latest_published_at":79},"Dev Tools","dev-tools",59,"2026-07-07T04:00:00.000Z",{"name":81,"slug":82,"count":83,"latest_published_at":84},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":86,"slug":87,"count":83,"latest_published_at":88},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":90,"slug":91,"count":92,"latest_published_at":93},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":95,"slug":96,"count":97,"latest_published_at":98},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":100,"slug":101,"count":102,"latest_published_at":103},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]