CoreWeave pricing

About

CoreWeave is a publicly traded (Nasdaq: CRWV) cloud-computing company that rents NVIDIA GPU and CPU compute to AI labs, hyperscalers, and enterprises. It has one of the more unusual origin stories in AI infrastructure: founded in 2017 as Atlantic Crypto, an Ethereum-mining operation run by three former commodities traders (Michael Intrator, Brian Venturo, and Brannin McBee). When crypto prices collapsed in 2018, the company bought up GPUs from distressed miners, rebranded to CoreWeave in 2019, and pivoted to renting that compute as a service — the same NVIDIA cards that turned out to be exactly what AI training needed.

That bet made CoreWeave one of the defining “neoclouds.” Revenue reached roughly $1.9B in 2024 and $5.13B in 2025 (up about 170% year over year), and the company went public on March 28, 2025 at $40.00 per share for an initial valuation near 23B. The catch is concentration: Microsoft was around 67% of 2025 revenue, OpenAI has contracted up to about $22.4B in total commitments, and Nvidia — CoreWeave’s primary GPU supplier — disclosed a roughly 7% stake in May 2025. CoreWeave’s economics are driven far more by a handful of large reserved contracts than by self-serve GPU rentals.

For current pricing, see CoreWeave’s pricing page.

Pricing summary : How CoreWeave’s pricing model works

CoreWeave is pure usage-based with a heavy commitment layer: you pay by the instance-hour for compute, with three purchasing motions stacked on top of each other:

1. On-Demand instances — self-serve, no commitment, published per-instance list rates for GPU and CPU nodes. Best for burst capacity.
2. Spot instances — interruptible capacity at roughly 40-60% off on-demand (e.g. HGX H100 spot at $19.71/hr vs $49.24 on-demand). Published openly.
3. Reserved / committed capacity — “up to 60% discounts over our On-Demand prices for committed usage,” quoted by sales. This is where the large AI-lab and hyperscaler contracts live, and it is the bulk of revenue.

Storage and networking are metered separately. Storage is openly priced (object storage from $0.06/GB/mo Hot down to $0.0125/GB/mo Archive; distributed file storage $0.070/GB/mo), and there are no ingress, egress, or data-transfer fees — a meaningful differentiator versus hyperscalers.

What makes this different: CoreWeave publishes a full portfolio-wide rate card — on-demand, spot, and inference single-GPU rates — for GPUs that most rivals gate behind sales calls, yet its actual revenue overwhelmingly comes from sales-quoted reserved contracts with a few mega-customers. The published card is a credibility and self-serve on-ramp; the business is large committed deals.

Pricing by product

On-demand GPU list prices (North America), per instance, June 2026. Most nodes are 8 GPUs, so the per-GPU rate is roughly the node price divided by 8:

GB300 NVL72 and HGX B300 on-demand are “contact sales.” Reserved/committed usage is up to 60% off these on-demand rates, sales-quoted.

Storage and networking (openly priced):

Sales motions across products: on-demand and spot are self-serve (published rates); reserved/committed capacity and Direct Connect are sales-led and quoted. CPU instances are also published (e.g. AMD Genoa from $6.42/hr on-demand).

Hidden costs : What CoreWeave users actually pay

CoreWeave’s networking is unusually clean (no egress, no transfer fees), but a realistic bill stacks several metered items beyond the headline GPU rate:

The biggest real-world cost driver is the reserved commitment itself: the discount (up to 60%) comes with a contractual obligation to pay for capacity over a multi-month or multi-year term, so idle committed GPUs are a sunk cost. The second is always-on storage — object and file storage meter continuously, independent of whether any instance is running. On-demand buyers should also watch the per-instance framing: the headline number is for a whole 8-GPU node, not a single GPU.

Want to estimate your own CoreWeave bill? Use the CoreWeave pricing calculator to model your costs based on usage patterns.

Pricing evolution : CoreWeave pricing history and changes

Cadence

Tracked range: 2024–present. CoreWeave’s IPO S-1 and investor disclosures are the cleanest public record of its economics; the live rate card is the source of current list prices.

Notable changes

• 2024 — Pre-IPO Hopper-era cloud: on-demand and reserved NVIDIA H100/A100 capacity, pitched at 30-60% below hyperscalers. Reserved contracts (sales-quoted) were the bulk of revenue.
• March 2025 — IPO on Nasdaq at $40.00/share, ~23B-dollar valuation. Disclosures revealed Microsoft at roughly two-thirds of revenue and a multibillion-dollar OpenAI commitment.
• June 2026 — Portfolio-wide rate card publishes on-demand, spot, and inference single-GPU prices across Blackwell, Hopper, and Ada/Ampere cards: HGX H100 $49.24/$19.71 (on-demand/spot), HGX B200 $68.80/$34.11, GB200 NVL72 $42.00. Reserved usage up to 60% off, sales-quoted.

The trajectory is from a quiet sales-quoted neocloud to a public company that publishes a full, transparent rate card while still earning most of its money from a few enormous committed contracts.

What’s unique : CoreWeave’s distinctive pricing mechanics

1. Three-motion stack on one rate card. CoreWeave publishes on-demand, spot, and inference single-GPU prices for the same hardware, then layers up-to-60% reserved discounts on top. Few neoclouds expose all three tiers openly.

2. Zero egress and transfer fees. No ingress, egress, internal-transfer, VPC, or NAT charges — removing the most unpredictable line items in a hyperscaler GPU bill and pricing connectivity almost entirely into the instance-hour.

3. Published list price, sales-quoted reality. The open rate card is a self-serve on-ramp and credibility signal, but the company’s economics are dominated by sales-quoted reserved contracts with a handful of mega-customers — a deliberate split between the shop window and the back room.

Strengths & weaknesses

Billing UX : CoreWeave billing controls and transparency

• Billing controls — Hourly metering for on-demand and spot; reserved/committed terms lock a lower per-hour rate via contract. Spot instances are interruptible, trading reliability for price.
• Usage visibility — CoreWeave runs as a managed Kubernetes platform (CKS) with its own observability and fleet/node lifecycle controllers; the control plane and SUNK scheduler are free, so cost visibility centers on instance-hours and storage.
• Payment options — Self-serve for on-demand/spot; sales-led contracts and invoicing for reserved capacity, Direct Connect, and enterprise. Storage and networking are itemized separately on the bill.

Strategic wins : Why CoreWeave’s pricing decisions worked

1. Undercutting hyperscalers with a transparent, egress-free card

By publishing per-instance rates 30-60% below AWS/Azure/GCP and eliminating egress fees, CoreWeave turned price and predictability into a wedge for AI workloads that move huge datasets. See how AI companies structure pricing.

2. Reserved commitments as the revenue engine

The up-to-60% committed discount converts spiky GPU demand into multi-year contracted revenue — the mechanism behind the Microsoft and OpenAI deals and the predictable backlog investors reward. Related: outcome-based pricing trends.

3. Spot + inference tiers to monetize spare capacity

Publishing spot prices (~40-60% off) and an inference single-GPU rate lets CoreWeave fill capacity between committed contracts, smoothing utilization. See choosing the right usage metric.

Areas to improve : Gaps in CoreWeave’s pricing approach

1. Per-instance framing obscures the per-GPU cost

A $49.24/hr HGX H100 sounds expensive until you realize it is eight GPUs (about $6.16 each); the rate card would be easier to compare if it showed per-GPU rates alongside node prices. See bill shock and cost unpredictability.

2. The best prices are still behind a sales call

On-demand and spot are public, but the up-to-60% reserved discounts — where most spend lands — are quoted, so buyers cannot self-estimate a committed contract without engaging sales.

3. Concentration risk is a pricing risk

With one customer near 67% of revenue, CoreWeave’s leverage in self-serve pricing is limited; the published card matters less than the terms negotiated with a few anchor tenants, which makes the public rate card more marketing than margin.

Key takeaways

1. CoreWeave is pure usage-based with a dominant commitment layer — hourly on-demand and spot, plus up-to-60% reserved discounts that carry most of the revenue. For the underlying model, see the introduction to usage-based pricing.
2. It publishes a fuller rate card than most neoclouds — on-demand, spot, and inference single-GPU prices openly listed — but the real economics are sales-quoted reserved contracts.
3. No egress or transfer fees is a genuine differentiator versus hyperscalers for data-heavy AI workloads.
4. Prices are per instance (mostly 8-GPU nodes), so headline numbers must be divided down to compare per-GPU against rivals like Lambda or RunPod.
5. Customer concentration is the real story — Microsoft ~67% of revenue and OpenAI’s ~$22.4B commitment mean a few mega-contracts, not the public card, define CoreWeave’s pricing power.

UBP implications

1. A public rate card and a sales-quoted core can coexist. CoreWeave shows you can publish on-demand/spot prices for credibility while running the business on negotiated committed contracts — the transparency is an on-ramp, not the monetization.
2. Commitment discounts convert volatility into backlog. Up-to-60% reserved pricing turns spiky GPU demand into multi-year contracted revenue, the metric public-market investors reward — a reusable pattern for any capacity-constrained usage business.
3. Removing punitive fees (egress) can be worth more than a lower unit rate. Zero data-transfer charges remove the least predictable line item in cloud bills, which buyers value even when the per-hour GPU rate is not the absolute cheapest.

Sources

• CoreWeave Cloud pricing (accessed 2026-06-15)
• CoreWeave Investor Relations (accessed 2026-06-15)
• CoreWeave announces pricing of IPO (accessed 2026-06-15)
• CNBC — CoreWeave begins trading on Nasdaq (accessed 2026-06-15)
• Sacra — CoreWeave revenue, valuation & funding (accessed 2026-06-15)
• Wikipedia — CoreWeave (history & founding, accessed 2026-06-15)

Bottom line

CoreWeave is a pure usage-based GPU cloud with a commitment-heavy core: it publishes on-demand, spot, and inference single-GPU rates openly (HGX H100 nodes at $49.24/hr, about $6.16/GPU/hr; spot ~60% cheaper; storage from $0.0125–$0.07/GB/mo with free egress), yet earns most of its money from up-to-60%-off reserved contracts that are sales-quoted. The numbers that matter most aren’t on the rate card — they’re in the IPO disclosures: $5.13B of 2025 revenue, ~67% from Microsoft and a ~$22.4B OpenAI commitment. The published card is the on-ramp; the mega-contracts are the business. Browse the pricing blueprint for more fully-researched company profiles, or compare CoreWeave against other Infrastructure, Compute & MLOps companies.