{"query":"open source vs open weight","topic":null,"geography":null,"count":1,"results":[{"schemaVersion":"2026-09-19","id":"guide:open-models:open-source-vs-open-weight","type":"guide","slug":"open-source-vs-open-weight","parentId":"guide:open-models","title":"Open-source AI vs open-weight AI","query":"open source vs open weight","answer":"Open-weight describes available learned parameters. Open-source AI is a broader claim about freedoms and the components needed to study, modify and share the system. Inspect weights, architecture, code, training information, evaluations and license terms separately.","scope":"Bright synthesis","topic":"open-source-vs-open-weight","topics":["open models","open-source-vs-open-weight"],"aliases":["open source vs open weight","open source AI","open source LLM","source available model","is open weight open source"],"intents":["compare open source and open weight","inspect reproducibility"],"geography":null,"locality":null,"sections":[{"id":"open-weight-ai","title":"Open-weight AI","answer":["A useful descriptive label for released model parameters. It says little on its own about rights, training code or data. Read the license and the artifact list separately."],"evidenceIds":["osi"],"canonicalUrl":"https://brightaifuture.com/open-models#openness"},{"id":"open-source-ai","title":"Open source AI","answer":["OSI’s definition asks for freedoms to use, study, modify and share, plus parameters, code and sufficiently detailed data information. It does not require every training datum to be redistributable. Bright shows the components rather than treating a download as certification."],"evidenceIds":["osi"],"canonicalUrl":"https://brightaifuture.com/open-models#openness"},{"id":"source-available","title":"Source-available","answer":["Source can be visible while its terms restrict use or redistribution. Availability and permission answer different questions. “Open” is used inconsistently across the industry; the actual artifacts and terms are the useful comparison."],"evidenceIds":["osi"],"canonicalUrl":"https://brightaifuture.com/open-models#openness"},{"id":"training-code-recipe-data","title":"Training code / recipe / data","answer":["Training code executes learning; a recipe records choices such as data processing and settings. Data information explains what went in. Access to the actual data is a separate question, including its rights and any gaps."],"evidenceIds":["osi"],"canonicalUrl":"https://brightaifuture.com/open-models#openness"}],"facts":[{"id":"open-source-vs-open-weight:answer","claim":"Open-weight describes available learned parameters. Open-source AI is a broader claim about freedoms and the components needed to study, modify and share the system. Inspect weights, architecture, code, training information, evaluations and license terms separately.","qualifier":"Bright synthesis from the cited documentation; sources support the component statements rather than supplying this sentence verbatim.","evidenceIds":["osi"]},{"id":"open-source-vs-open-weight:open-weight-ai","claim":"A useful descriptive label for released model parameters. It says little on its own about rights, training code or data. Read the license and the artifact list separately.","qualifier":"Definition and Bright editorial interpretation.","evidenceIds":["osi"]},{"id":"open-source-vs-open-weight:open-source-ai","claim":"OSI’s definition asks for freedoms to use, study, modify and share, plus parameters, code and sufficiently detailed data information. It does not require every training datum to be redistributable. Bright shows the components rather than treating a download as certification.","qualifier":"Definition and Bright editorial interpretation.","evidenceIds":["osi"]},{"id":"open-source-vs-open-weight:source-available","claim":"Source can be visible while its terms restrict use or redistribution. Availability and permission answer different questions. “Open” is used inconsistently across the industry; the actual artifacts and terms are the useful comparison.","qualifier":"Definition and Bright editorial interpretation.","evidenceIds":["osi"]},{"id":"open-source-vs-open-weight:training-code-recipe-data","claim":"Training code executes learning; a recipe records choices such as data processing and settings. Data information explains what went in. Access to the actual data is a separate question, including its rights and any gaps.","qualifier":"Definition and Bright editorial interpretation.","evidenceIds":["osi"]}],"limitations":["The term “open” is used inconsistently; the actual artifacts and permissions control reuse.","Bright does not certify a model under a legal definition."],"evidence":[{"id":"osi","title":"OSI · Open Source AI Definition 1.0","url":"https://opensource.org/ai/open-source-ai-definition","note":"Primary documentation supporting the attached definitions and claims.","provenance":"institutional-report","supports":["open-source-vs-open-weight:answer","open-source-vs-open-weight:open-weight-ai","open-source-vs-open-weight:open-source-ai","open-source-vs-open-weight:source-available","open-source-vs-open-weight:training-code-recipe-data"]}],"relatedResources":[{"type":"guide","id":"guide:open-models","title":"Open Models","url":"https://brightaifuture.com/open-models"}],"canonicalUrl":"https://brightaifuture.com/open-models#openness","markdownUrl":"https://brightaifuture.com/read/open-models.md","lastReviewedAt":"2026-09-19","publicationDate":"2026-09-19","lastUpdatedAt":null,"methodology":"Bright synthesis from the cited primary and institutional sources. Source checks are not independent replication, legal advice, engineering review, or a local impact determination."}]}