--- title: "From Models to Products: LLMs for Recommendation at Spotify Scale" url: https://daily.dev/posts/from-models-to-products-llms-for-recommendation-at-spotify-scale-rnpxxwmdh source_url: https://research.atspotify.com/2026/8/from-models-to-products-llms-for-recommendation-at-spotify-scale type: article source: "Spotify Research" published: 2026-08-03T06:10:54.942Z updated: 2026-08-03T06:11:19.346Z tags: ["machine-learning", "llm", "spotify"] reading_time: 11 upvotes: 0 comments: 0 language: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # From Models to Products: LLMs for Recommendation at Spotify Scale **[Spotify Research](https://daily.dev/sources/spotify_research)** · 11 min read · 0 upvotes · 0 comments ## Summary Spotify Research presents two complementary systems for LLM-based recommendation at scale, both accepted at KDD 2026. NEO is a unified, language-steerable model that handles recommendation, search, explanation, and user understanding within a single set of weights by treating catalog items as Semantic IDs — discrete tokens derived from item content. GLIDE is a production 1B-parameter LLM deployed for podcast discovery, introducing the concept of non-habitual listening and combining short-term history with dense long-term user embeddings as soft tokens. In a 21-day A/B test covering ~20 million impressions, GLIDE increased non-habitual podcast listening by 5.4% and new-show discovery by 14.3%. Both systems rely on staged training, beam-search decoding, and hybrid evaluation combining offline metrics, human judges, and LLM-based judges to bridge the gap between retrieval accuracy and real recommendation quality. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Teaching Large Language Models to Speak Spotify: How Semantic IDs Enable Personalization](https://daily.dev/posts/teaching-large-language-models-to-speak-spotify-how-semantic-ids-enable-personalization-i4u6pcpnq) · Spotify Research · 1 upvotes · 0 comments - [Profile-aware LLM-as-a-Judge for Podcasts: A Better Middle Ground Between Offline Metrics and A/B Tests](https://daily.dev/posts/profile-aware-llm-as-a-judge-for-podcasts-a-better-middle-ground-between-offline-metrics-and-a-b-te-8karfizw2) · Spotify Research · 0 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#llm](https://daily.dev/tags/llm), [#spotify](https://daily.dev/tags/spotify) [View this post on daily.dev](https://daily.dev/posts/from-models-to-products-llms-for-recommendation-at-spotify-scale-rnpxxwmdh)