{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/open-magvit2-an-open-source-project-toward","title":"Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation","arxiv_id":"2409.04410","date":"2024-09-06","proceeding":null,"authors":["Zhuoyan Luo","Fengyuan Shi","Yixiao Ge","Yujiu Yang","LiMin Wang","Ying Shan"],"abstract":"We present Open-MAGVIT2, a family of auto-regressive image generation models ranging from 300M to 1.5B. The Open-MAGVIT2 project produces an open-source replication of Google's MAGVIT-v2 tokenizer, a tokenizer with a super-large codebook (i.e., $2^{18}$ codes), and achieves the state-of-the-art reconstruction performance (1.17 rFID) on ImageNet $256 \\times 256$. Furthermore, we explore its application in plain auto-regressive models and validate scalability properties. To assist auto-regressive models in predicting with a super-large vocabulary, we factorize it into two sub-vocabulary of different sizes by asymmetric token factorization, and further introduce \"next sub-token prediction\" to enhance sub-token interaction for better generation quality. We release all models and codes to foster innovation and creativity in the field of auto-regressive visual generation.","url_abs":"https://arxiv.org/abs/2409.04410v2","url_pdf":"https://arxiv.org/pdf/2409.04410v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"open-magvit2-an-open-source-project-toward","repo_url":"https://github.com/tencentarc/seed-voken","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"open-magvit2-an-open-source-project-toward","repo_url":"https://github.com/tencentarc/open-magvit2","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"image-generation","task_name":"Image Generation"},{"task_slug":"image-reconstruction","task_name":"Image Reconstruction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/image-generation-on-imagenet-256x256","task":"Image Generation","dataset":"ImageNet 256x256","model":"Open-MAGVIT2-XL","rank_in_archive_order":57,"of":94,"metrics":{"FID":"2.33"},"uses_additional_data":false},{"leaderboard":"/sota/image-reconstruction-on-imagenet","task":"Image Reconstruction","dataset":"ImageNet","model":"Open-Magvit2 (16x16)","rank_in_archive_order":8,"of":15,"metrics":{"FID":"1.17","PSNR":"21.90"},"uses_additional_data":false},{"leaderboard":"/sota/image-reconstruction-on-ultra-high-resolution","task":"Image Reconstruction","dataset":"Ultra-High Resolution Image Reconstruction Benchmark","model":"Open-Magvit2 (16x16)","rank_in_archive_order":3,"of":6,"metrics":{"PSNR":"23.91","rFID":"4.18"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2409.04410","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2409.04410"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/tencentarc/seed-voken","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/tencentarc/open-magvit2","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran_violates":2,"ran_draft_wrong":1},"by_repo_kind":{"official":{"samples":2,"ran":2,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"935e50ad10badd9b","entry":"check_image","repo":"tencentarc/seed-voken","repo_kind":"official","path":"src/Open_MAGVIT2/data/prepare_pretrain.py","file_url":"https://github.com/tencentarc/seed-voken/blob/HEAD/src/Open_MAGVIT2/data/prepare_pretrain.py","link_basis":"first_harvest_node","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"935e50ad10badd9b"}},{"code_sha256_prefix":"d35f32440fc28b88","entry":"check_tar_file","repo":"tencentarc/seed-voken","repo_kind":"official","path":"src/Open_MAGVIT2/data/prepare_pretrain.py","file_url":"https://github.com/tencentarc/seed-voken/blob/HEAD/src/Open_MAGVIT2/data/prepare_pretrain.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"d35f32440fc28b88"}},{"code_sha256_prefix":"4cb732f513d69dfd","entry":"disabled_train","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"4cb732f513d69dfd"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}