@Walrus 🦭/acc #Walrus In the fast‑evolving world of decentralized storage, Quilt represents the latest milestone in the growth of the Walrus Protocol — a data infrastructure layer built on the Sui blockchain designed to power Web3 applications with secure, scalable, and efficient storage. Quilt specifically addresses one of the biggest challenges developers face in decentralized systems: cost‑effective, high‑performance handling of a large volume of small files.
Since Walrus’s mainnet launch in March 2025, the protocol has attracted substantial adoption, housing over 800 TB of encoded data across 14 million blobs and supporting a diversity of real‑world projects from digital media archives to decentralized compute and NFT ecosystems. However, early adopters discovered that while storing large files is highly efficient on Walrus, large numbers of small files presented overhead and cost inefficiencies that required manual batching by developers. Quilt was created to solve exactly that.
What Quilt Is and Why It Matters
Quilt is a native batch storage solution built into the Walrus infrastructure. Rather than treating each small file — such as NFT image assets, log records, AI communication data, or tiny documents — as an individual storage operation, Quilt bundles many small files into a single logical unit. This dramatically reduces storage overhead and associated gas costs on Sui and Walrus. For example, storing many 10 KB blobs individually could incur up to 420× more storage cost than storing them in a Quilt, while 100 KB blobs see around 106× savings.
By grouping up to roughly 660 files per Quilt, developers no longer need to manually bundle files before sending them to Walrus. Instead, Quilt’s API lets them efficiently manage large datasets of small files with far less operational complexity — and significantly lower cost. This makes Walrus a unified, versatile storage platform for data of any size.
Developer Experience and Performance
Quilt’s intuitive API is designed to be Walrus‑native — developers can integrate batch storage directly into their applications without bespoke batching schemes. Despite the consolidation of files, each file remains individually accessible through lightweight identifiers, avoiding the need to “unpack” the entire storage unit to retrieve a single item. This means apps can deliver fast, interactive performance, even when managing millions of small assets.
A key enhancement Quilt brings is built‑in metadata support. Developers can attach immutable, custom metadata — such as tags or identifiers — directly alongside each file within a Quilt. This enables smarter search, filtering, and retrieval without needing separate on‑chain metadata lookups, simplifying logic and reducing costs while improving developer productivity.
Real‑World Adoption and Use Cases
Projects already testing or adopting Quilt include Tusky, a privacy‑focused decentralized storage platform that uses Quilt to optimize its handling of small file uploads and reduce overhead during high‑volume periods. Other builders like Gata, a decentralized AI execution infrastructure, are also using Quilt’s batch API to organize vast datasets efficiently.
Practical applications for Quilt span a variety of domains:
User‑generated content in social and messaging apps, where many small files are created daily.
NFT collections with hundreds or thousands of tiny media files and metadata.
AI agent data and logs, where frequent communication and event data require efficient storage and retrieval.
The Future of Decentralized Data
Quilt’s launch — live on Walrus Testnet and expected on Mainnet with version 1.29 — marks a pivotal step in realizing Walrus’s vision as a comprehensive data layer for the decentralized internet. By unlocking cost savings, simplifying the developer experience, and making small file storage truly scalable, Quilt positions Walrus not just as a tool for large media, but as a full‑spectrum storage solution for Web3 builders of all kinds.
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