@ClementDelangue: AI teams shouldn’t have to choose between expensive object storage and painful git workflows. @huggingface Storage is b…

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Summary

Hugging Face launches Storage Buckets, a purpose-built storage solution for AI teams offering per-TB pricing, built-in CDN, and Xet deduplication for model weights, datasets, and checkpoints.

AI teams shouldn’t have to choose between expensive object storage and painful git workflows. @huggingface Storage is built for model weights, datasets, checkpoints and artifacts: - simple per-TB pricing - built-in CDN - Xet deduplication - private by default when needed Store your AI data where your AI work already happens:
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Cached at: 05/17/26, 03:27 AM

AI teams shouldn’t have to choose between expensive object storage and painful git workflows.

@huggingface Storage is built for model weights, datasets, checkpoints and artifacts:

  • simple per-TB pricing
  • built-in CDN
  • Xet deduplication
  • private by default when needed

Store your AI data where your AI work already happens:


Storage - Hugging Face

Source: https://huggingface.co/storage

Hugging Face Storage BucketsStorage Buckets

Store models, datasets, and artifacts with simple per-TB pricing. Built-in CDN, Xet deduplication, and no git overhead.

Trusted by more than10,000AI teams

Storage

Storage built for AI teams

Store models, datasets, and artifacts with simple per-TB pricing. Xet deduplication. Included CDN. No git overhead.

  • Per-TB pricing with built-in CDN and deduplication speedups.
  • No Git constraints: commit-free sync and fast object updates.
  • Designed for ML workflows: datasets, checkpoints, model artifacts.

Xet Technology

Next-gen large-scale storage for AI

Xet uses content-defined chunking to break files into byte-level chunks and deduplicates across your entire bucket. When you retrain a model and only 5% of weights change, only that 5% is re-uploaded.

  • Raw + processed dataset: stored once, billed once*
  • 4x less data per upload, verified with real-world workloads

*RequiresEnterprise or Enterprise Plusplan

Pricing

Transparent, volume-based pricing

Simple per-TB pricing that scales with usage. Egress and CDN are included at no extra cost.

Data Storage

Assemble training data at any scale

Pour raw data from every source into a single bucket: crawls, annotations, synthetic outputs, partner datasets. No git overhead, no commit queues, no file-count limits. When training begins, your data is already there, streamed to GPUs via the included CDN.

  • Immediate availability on upload, no queued commits
  • Batch API processes thousands of files in a single call
  • Raw + processed datasets with dedup = no double billing*

*RequiresEnterprise or Enterprise Plusplan

CDN

Built-in CDN for blazing fast access

Every bucket includes a CDN. Warm localized cache close to where you compute for ultra fast streaming and downloads. Egress is included up to a generous 8:1 ratio of your total storage.

  • Pre-warm cache in any cloud region you need
  • Our CDN is deployed inside GCP and AWS networks
  • Egress included up to 8:1 your storage

More providers coming soon

Coding Agents

Give your coding agents persistent storage

Coding agents run in ephemeral environments, but their outputs shouldn’t vanish. Checkpoints, benchmark results, generated datasets: onehf synccommand in your agent’s bash tool is all it takes.

  • Pre-warmed CDN and no git overhead for fast reads and writes
  • Persist artifacts across ephemeral CI runs and terminal sessions
  • Install the officialHF CLI skilland your agent knows every command

AES-256 Encryption

End-to-end encryption at rest and in transit

Audit Logs

Full visibility into every access event

SSO & RBAC

Enterprise SSO with role-based access control

US & EU Regions

Choose where your data lives

SOC 2 Type II|GDPR Compliant

Get started withHF Storage BucketsHF Storage Buckets

Start with buckets, sync your AI data, and unlock object storage built for ML workflows.

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Introducing Storage Buckets on the Hugging Face Hub

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Hugging Face introduces Storage Buckets, a new mutable, S3-like object storage feature on the Hub optimized for production ML workflows using its Xet backend for efficient deduplication.