CoreWeave Launches Flexible Capacity Plans to Accelerate AI Innovation
New unified consumption framework aligns capacity with modern AI workload patterns
CoreWeave, The Essential Cloud for AI™, today announced CoreWeave Flexible Capacity Plans, including Flex Reservations and Spot, designed to match the dynamic reality of modern AI workloads. With Flex Reservations and Spot, CoreWeave enables customers to move beyond the binary choice of reserved capacity versus on-demand capacity.
While AI training cycles are often predictable, production-level inference is not. Traffic spikes and use fluctuates, forcing teams to either over-provision or risk delays. CoreWeave Flexible Capacity Plans give teams cost-efficient options for interruptible work and more control over how they run AI, enabling innovation without limitation.
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“At production scale, infrastructure planning becomes as critical as deployment,” said Chen Goldberg, EVP of Product & Engineering at CoreWeave. “CoreWeave is setting the standard for the AI cloud by providing guaranteed capacity when it counts and flexible pricing when demand shifts. We’re bringing the original promise of the cloud – scale and efficiency – back to the AI pioneers pushing the limits of innovation.”
A Unified Capacity Framework for AI
CoreWeave Flexible Capacity Plans build on CoreWeave’s existing Reservations and On-Demand offerings, extending that foundation to reflect how modern AI workloads actually behave.
With the addition of Flex Reservations and Spot, CoreWeave introduces a unified capacity framework that redefines how production AI runs at scale:
- Reservations: Predictable, always-on capacity for steady workloads.
- Flex Reservations: A first-of-its kind model for guaranteed peak capacity with flexible economics for workloads that ramp or scale unevenly. Customers secure a capacity ceiling with a lower 24/7 holding fee, paying full usage rates only when instances are active.
- Spot: A new lower-cost option for interruption-tolerant work like batch analytics or backfills. Spot is delivered with explicit preemption signaling, allowing engineers to checkpoint and recover work cleanly.
- On Demand: Best-effort access for immediate, incremental capacity.
This framework allows customers to reserve what’s steady, protect what must be guaranteed, and shift interruptible work — aligning cost and certainty with real demand patterns. Flexibility of this kind isn’t theoretical; it’s already shaping how customers design and scale their AI workflows.
“At inference.net, our mission is to help teams get the most from AI models,” said Ibrahim Ahmed, CTO at inference.net. “ The most powerful AI models are not generic, off-the-shelf models, they’re specialized models trained on your data, for your problem. We built custom scheduling and orchestration software so that any team can train and deploy frontier-quality specialized LLMs on underutilized GPU capacity. Spot instances from CoreWeave are key to making this possible, giving our customers access to the compute they need to bring custom models to production at a fraction of the cost.”
Flex Reservations are available to Preview through CoreWeave account teams in eligible regions and SKUs, and Spot is generally available now.
CoreWeave’s AI cloud delivers industry-leading performance and efficiency through an end-to-end technology stack optimized for modern AI workloads. CoreWeave’s technology team consistently sets new standards for performance, demonstrated by an industry-leading MLPerf benchmark for AI workloads and its position as the only AI cloud to earn the top Platinum ranking in both SemiAnalysis ClusterMAX™ 1.0 and 2.0, which evaluate AI cloud performance, efficiency and reliability.
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