Per-GB Storage Pricing: Examples & Companies

What is it

Per-GB storage pricing is a billing unit where customers are charged per gigabyte of data stored on the platform per month.

Storage is the persistent-state dimension of cloud pricing. Where compute meters time and APIs meter requests, the storage meter captures data at rest — the bytes that survive between sessions and keep occupying disk whether or not anything is actively running against them. The unit is almost always expressed as a rate per gigabyte over a billing window, most commonly a GB-month, though marketplace vendors like Vast.ai bill it per GB-hour for finer-grained, continuous accounting.

The model shows up in two distinct places in the corpus. The first is cloud and GPU infrastructure, where storage is a secondary meter layered on top of per-second or per-hour compute: RunPod, Modal, E2B, and Lightning AI all bill persistent disk separately from the machines that use it. The second is data and retrieval platforms — vector databases and serverless search — where the stored index is the product. Upstash and turbopuffer both meter stored data per GB because the embedding corpus a customer holds is the asset they pay to keep online.

The defining characteristic of per-GB storage pricing is that the rate is low but compounds. A few cents per gigabyte feels negligible at signup, but storage never sleeps: unlike a paused container or an idle endpoint, retained data keeps accruing charges for as long as it exists. That asymmetry — cheap per unit, relentless over time — is what makes storage the line item buyers most often underestimate.

How it works

The core formula is simple: a vendor measures how much data a customer is keeping, multiplies it by a per-GB rate, and prorates it over the billing window. The variation lives in three dimensions — the time basis, the storage class, and the free allowance.

The headline rates cluster in a narrow band. Block and network disk at GPU vendors runs roughly $0.05–$0.20/GB-month — RunPod prices Network Storage at $0.05–$0.14/GB-month and Volume Disk at $0.10–$0.20/GB-month. Database storage sits a notch higher: Upstash charges a flat $0.25/GB across Redis, Vector, and Search Fixed/Pro plans. The cheapest effective rates come from object-storage architectures — turbopuffer builds directly on S3-class storage to undercut memory-resident vector databases by an order of magnitude.

Unit math: Monthly storage bill = (stored_GB − free_allowance_GB) × rate_per_GB_month. On Upstash Redis, keeping 50 GB costs (50 − 1) × $0.25 = $12.25/mo on top of per-command charges.

The subtlety is when the meter runs. GB-month vendors snapshot or average your volume across the month. Vast.ai’s per-second model is stricter: storage accrues for every second an instance exists, including while it is stopped, so the only way to stop paying is to delete the instance. Upstash softens this with a daily-average basis, so a brief spike in stored data doesn’t set a high-water mark for the whole period. For buyers, the time basis matters as much as the headline rate — a “cheaper” GB-hour rate that bills paused resources can cost more than a higher GB-month rate that doesn’t.

Companies using this

Fifteen companies in the corpus meter storage per GB, spanning GPU and sandbox infrastructure (RunPod, Modal, Vast.ai, E2B, Lightning AI), data and retrieval platforms (Upstash, turbopuffer, Vectara), and platform products that fold storage into a broader credit or compute-unit model (Apify, Dify). The table below lists all of them with their pricing model and other billing units.

Patterns observed

Across the fifteen companies, per-GB storage almost never stands alone — it is the third or fourth meter in a stack, and how it’s positioned reveals the vendor’s product shape.

• Storage is a secondary meter at compute vendors. For RunPod, Modal, E2B, Lightning AI, and Vast.ai, the headline product is per-second or per-hour GPU/CPU time; storage is the line item that captures the state customers want to keep between runs. E2B’s pricing history is telling — its per-vCPU compute rates and $150/mo Pro fee stayed fixed for the entire tracked range, but RAM and storage were added as separate meters ($0.0000045/GiB/s) once customers needed persistent sandboxes.
• Storage is a primary meter at retrieval platforms. At Upstash and turbopuffer, the stored index is the product, so storage sits alongside requests/queries as a co-equal usage axis. turbopuffer goes furthest by making cheap object storage its entire architectural bet against in-memory rivals.
• Free allowances are small and deliberate. Upstash (1 GB Redis free) and E2B (1 GiB Hobby, 5 GiB Pro) include just enough storage to remove signup friction without giving away the persistent layer. These are onboarding grants, not generous tiers.
• Storage tiers proliferate by durability. RunPod’s three-way split — Container Disk, Volume Disk, Network Storage — shows vendors charging different rates for ephemeral vs. persistent vs. network-attached durability, the same way hyperscalers separate instance store from block volumes.
• Rates are publicly stated more often than gated. Most vendors print the per-GB number on the page. The exception is enterprise RAG: Vectara folds storage into a credit unit and never publishes per-GB overage rates, surfacing storage only inside its console’s Usage tab.

Counterexamples & variants

The clearest variant is the gated rate. turbopuffer meters storage per GB-month and writes per GB written, but the base per-GB rate appears only inside its interactive cost calculator — the static pricing page does not expose it. The corpus records this as “unknown” rather than guessing, which is itself instructive: a usage-based vendor can lean entirely on storage economics for its competitive story (object storage vs. RAM) while keeping the actual rate behind a calculator, so buyers must model their own corpus to learn the number.

The second variant is storage absorbed into a synthetic unit. Apify bills compute units at $0.13–$0.20 per CU and Dify and Genspark use credits — in these models storage consumption is real but is rolled into the abstract unit rather than billed as raw GB. The customer still pays for data at rest, but the per-GB rate is invisible, converted into the platform’s own currency. This trades transparency for simplicity and is common where storage is a small fraction of total cost.

The sharpest counterexample to “storage is cheap and passive” is Vast.ai. Because it bills storage continuously per second — including on stopped instances — a customer who spins down a GPU to save on compute keeps paying for the attached disk indefinitely. Deleting the instance is the only way to stop the meter. This inverts the usual mental model where pausing a resource pauses its cost, and it’s the most common surprise on the bill. The enterprise RAG case (Vectara) is the opposite failure: storage is metered but its rate is never published, so buyers cannot self-estimate where a deployment lands and must negotiate the size band per deal.

What this means for buyers vs vendors

For buyers

Treat the per-GB rate as the least important storage variable. Ask three questions instead: What is the time basis (GB-month, GB-hour, or daily-average)? Does the meter keep running on stopped or idle resources — as it does on Vast.ai? And are there minimum billable floors, like turbopuffer’s 1.28 GB-per-query minimum? Storage compounds silently, so model it over the full retention period, not just month one, and use the guide to choosing the right usage metric to weigh whether storage or requests will dominate your bill. Where rates are gated (turbopuffer) or bundled into credits (Vectara), insist on a worked estimate for your own data volume before committing.

For vendors

Per-GB storage works best as a secondary meter that captures persistent state without distorting your primary value metric — the pattern RunPod, Modal, and E2B follow by keeping compute as the headline. Decide your time basis deliberately: daily-average (like Upstash) reduces bill-shock from spikes, while per-second continuous metering (like Vast.ai) maximizes capture but generates support tickets when customers don’t realize stopped instances still cost money. A small free allowance removes onboarding friction cheaply. For the mechanics of metering and prorating data at rest across a billing cycle, see the guides on usage-based pricing models and usage invoicing and billing cycles.