Papers › Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation
Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation
Zhuoyan Luo, Fengyuan Shi, Yixiao Ge, Yujiu Yang, LiMin Wang, Ying Shan
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., 2¹⁸ codes), and achieves the state-of-the-art reconstruction performance (1.17 rFID) on ImageNet 256 ×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.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Image Generation | ImageNet 256x256 | Open-MAGVIT2-XL | FID | 2.33 | #57 of 94 | Archive leaderboard | report |
| Image Reconstruction | ImageNet | Open-Magvit2 (16x16) | FID | 1.17 | #8 of 15 | Archive leaderboard | report |
| Image Reconstruction | ImageNet | Open-Magvit2 (16x16) | PSNR | 21.90 | #8 of 15 | Archive leaderboard | report |
| Image Reconstruction | Ultra-High Resolution Image Reconstruction Benchmark | Open-Magvit2 (16x16) | PSNR | 23.91 | #3 of 6 | Archive leaderboard | report |
| Image Reconstruction | Ultra-High Resolution Image Reconstruction Benchmark | Open-Magvit2 (16x16) | rFID | 4.18 | #3 of 6 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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