Vercel Blob is available across all 20 of Vercel’s compute regions, but “multi-region” here means you can pin each store to one region, not that a single store replicates across them. A global CDN of 126 Points of Presence in 94 cities fronts that one region, with no documented cross-region strong-consistency guarantee.
What does multi-region actually mean for Vercel Blob?
Vercel Blob is a single-region store behind a global cache, not a geo-replicated object store: each blob lives in exactly one region chosen at store-creation time, and the rest of the world reaches it through Vercel’s CDN. The Vercel regions documentation describes 126 Points of Presence across 94 cities and 51 countries backing 20 compute-capable regions, with PoPs routing to the nearest region over a private network at single-digit-millisecond latency. That is a delivery topology, not a replication topology. The blob still exists in one place.
This is the gap most changelog-shaped coverage skips. “Available in every region” reads like a geo-distribution feature, and in the narrow sense it is, since you can place data where your writers live. But there is no documented mechanism by which a single store’s objects fan out to live copies in other regions. If a function in Frankfurt reads a blob pinned to Washington, a cache miss traverses back to the Washington origin, because that is where the object actually sits. The latency story is real; the consistency story is implicit, and it is the more interesting half of the tradeoff.
Which regions can a Blob store live in, and can you change it later?
Each Blob store is pinned at creation time to one of Vercel’s 20 compute-capable regions, and the region is immutable for the life of the store; you cannot migrate it in place. You choose via the dashboard region selector or the CLI --region flag, and the choice is final. Relocating data means creating a new store in the target region and copying blobs over.
That immutability carries two consequences. The first is data residency: if a workload needs objects to rest in a specific jurisdiction, the pin gives you that guarantee. The second is that the region choice quietly shapes the read path. Co-locating your functions with the store is the lowest-latency configuration; every reader outside that region pays the cross-region hop on a cache miss.
How fast do reads propagate across regions?
Reads are CDN-cached for up to one month by default. After an overwrite or delete, cross-region readers may see a stale copy for some period; the cache invalidation window for deletes and overwrites is not explicitly documented. The documented remedy is cache-busting: append a query string to the blob URL to force a fresh fetch.
The cache layer is separate from durability. Blob reached general availability on S3 infrastructure in May 2025 with 99.999999999% durability. That figure describes object-store fault tolerance, not cache replication latency. Vercel Blob does not publish a cross-region write-propagation SLA; the CDN cache is a read-path layer, not a geo-replication mechanism.
The cost model reinforces the cache-friendly design. Cache HITs do not count as Simple Operations or incur Fast Origin Transfer charges, and cacheControlMaxAge tunes the TTL up to the one-month ceiling. Regional cache locality is therefore both a latency lever and a cost lever: a warm cache near your readers serves fast and cheap, while a cold cache pays the origin transfer every time. That coupling is why the write-path decisions in the next two sections matter as much for the bill as for correctness.
How do concurrent writes coordinate?
Each store has a single origin region, so write coordination reduces to standard single-region object storage semantics. Multiple writers targeting the same key race at the origin; the application is responsible for any ordering guarantees it needs. There is no documented cross-region strong-consistency guarantee: a write at the origin becomes visible to other regions through the CDN on cache refresh, not synchronously.
For a single-writer workload this is straightforward: one origin, one source of truth, the CDN absorbing read load. For concurrent writers in different regions hitting the same key, the origin is the arbitration point, but writes are not made visible to other regions any faster than the cache allows.
What does multi-region Blob cost?
The pricing documentation draws a deliberate line: Blob Data Transfer ($0.050/GB, roughly three times more cost-efficient than Fast Data Transfer on average) is the cheap tier for bulk media; Fast Data Transfer is the low-latency tier; which one a read incurs depends on whether it hits the cache. Storage runs $0.023/GB-month, and operations bill across two tiers at $0.40 and $5.00 per million.
The sharp edge is the cache ceiling. Blobs larger than 512 MB are never cached and always register as cache misses, incurring a Fast Origin Transfer and Edge Request charge on every access. For a multi-region media workload serving large files, that is a hard ceiling, not a soft one: there is no tuning that makes a 600 MB blob cacheable, so every read from every region pays the origin transfer. The never-cached rule means large objects above that ceiling are the expensive case.
It is worth separating three ideas that marketing-adjacent framing tends to blur.
| Concept | What it actually is | What it is not |
|---|---|---|
| Region pinning | Choosing where one store lives, at creation | A live-migration tool; the choice is immutable |
| Blob Data Transfer | A cost tier for serving from regional hubs ($0.050/GB) | Automatic geo-replication of one store |
| Cache invalidation | A CDN layer covering reads with up to a one-month TTL | An S3 replication SLA or a consistency bound |
How should you architect Blob across regions?
Pin one store near your writers, fan reads out through the CDN, and design around cache-busting query strings rather than assuming instant propagation. For workloads that need genuine geographic distribution of the data itself, the only structural lever is to run more than one store, each pinned to a different writer region, with application-layer reconciliation. Vercel does not replicate a single store for you.
A few concrete patterns fall out of the model. For single-region apps, colocate the function and the store and let the CDN absorb the reads; this is the cheapest and simplest shape. For multi-region writers, keep a store in each writer region and reconcile at the application layer, using application-level coordination to avoid stomping concurrent updates. For read-heavy public media, lean on long cacheControlMaxAge values and cache-busting tokens on the URL to invalidate, since both private and public blobs cache for up to one month.
The freshly-default OIDC authentication, which replaced the long-lived BLOB_READ_WRITE_TOKEN for newly connected projects on 2026-06-01, fits this shape: scoped, short-lived credentials are what you want when you are stamping out per-region stores rather than sharing one long-lived token. The recent CLI blob-URL signing entry, landed 2026-06-22, rounds out the operator story for teams that need signed delivery from the command line without round-tripping through the dashboard. Neither change alters the underlying model (one region per store, a global cache in front, a single-origin write path), but together they make the multi-store pattern easier to operate.
The latency-versus-consistency tradeoff has always been there. What changed is that the tooling now assumes you will want to act on it.
Frequently Asked Questions
What API primitive handles concurrent writes to the same blob key?
Vercel Blob exposes ETag-based optimistic concurrency via the ifMatch option on put(), copy(), and del(). A mismatch throws BlobPreconditionFailedError, letting the caller retry with fresh state. There is no row-level lock or transaction primitive; ifMatch is the only write-coordination tool the API provides.
What is Vercel’s default function region, and how does it affect Blob latency?
Vercel Functions default to iad1 (Washington, D.C.) unless you override the region setting. A Blob store pinned to any other region will hit the origin on every cache miss from a default-region function, so teams that never set an explicit function region may be paying the cross-region hop without realizing it.
Is there a maximum individual file size for Vercel Blob?
Individual blobs cap at 5 TB per file. Below 512 MB, objects cache for up to a month; above 512 MB, caching is disabled entirely. For multi-region delivery, the 512 MB threshold is the cost boundary most workloads hit first, not the 5 TB ceiling.
How does this compare to S3 Cross-Region Replication for teams that need sub-second consistency across geographies?
S3 Cross-Region Replication keeps live copies in multiple buckets with configurable replication-time controls and SLA-backed propagation. Vercel Blob has no equivalent: one store, one origin, and cross-region reads served from CDN cache rather than a replica. Teams that need sub-second cross-region consistency must run multiple Blob stores and reconcile at the application layer, a heavier operational lift than enabling an S3 replication rule.
