CoreWeave vs Nebius
ComparisonCoreWeave and Nebius are two of the most prominent GPU neoclouds challenging hyperscalers for dominance in AI infrastructure. Both companies have experienced extraordinary growth through 2025 and into 2026, but they represent fundamentally different strategies for capturing the GPU cloud market. CoreWeave, the US-based powerhouse that IPO'd on Nasdaq in March 2025, topped $5.1 billion in annual revenue and amassed a $66.8 billion backlog. Nebius, spun out of Yandex's international operations, secured a landmark $17.4 billion GPU-as-a-service contract with Microsoft and a $2 billion strategic investment from NVIDIA.
The comparison between these two companies illuminates a broader structural shift in cloud computing: the rise of specialized, GPU-first infrastructure providers that can deliver better performance and pricing than general-purpose hyperscalers for AI workloads. CoreWeave has established itself as the infrastructure backbone for frontier AI labs, while Nebius is building a vertically integrated, full-stack AI cloud with strong European roots and an expanding global footprint. Choosing between them depends on where you are, what you're building, and how much of the stack you want managed for you.
Feature Comparison
| Dimension | CoreWeave | Nebius |
|---|---|---|
| 2025 Revenue | $5.13 billion (738% YoY growth in 2024, continued hypergrowth) | ~$200M+ run-rate; $17.4B Microsoft contract and $3B Meta deal secured |
| GPU Fleet Scale | ~250,000+ GPUs; 1.6 GW of contracted power | 35,000–60,000 GPUs (2025); targeting 240,000 GPUs mid-term; 2.5 GW contracted by end of 2026 |
| Latest GPU Offerings | NVIDIA HGX B300, GB200 NVL72; Vera Rubin NVL72 planned for H2 2026 | NVIDIA GB300 NVL72, GB200 NVL72, HGX B200, H200, H100, L40S |
| H100 Pricing (On-Demand) | ~$4.76/GPU/hr (HGX nodes ~$6.15/GPU/hr bundled) | ~$2.95/GPU/hr (HGX H100) |
| Data Center Regions | US-focused (multiple facilities across the United States) | Finland, UK, Iceland, France, US (New Jersey, Kansas City) |
| Managed Services | Mission Control for fleet management; Kubernetes support; Flex Reservations and Spot (March 2026) | Managed Kubernetes, PostgreSQL, Nebius AI Studio (inference APIs for open models), Slurm orchestration, Capacity Dashboard |
| Vertical Integration | GPU infrastructure and platform layer; partners for higher-stack tooling (e.g., Weights & Biases) | Full-stack: custom server rack design, managed services, AI Studio inference APIs, Toloka data labeling |
| Key Customers | OpenAI, IBM, Microsoft, major AI labs | Microsoft ($17.4B deal), Meta ($3B deal) |
| Strategic Partnerships | NVIDIA preferred cloud partner; deep integration with AI lab ecosystem | NVIDIA $2B strategic investment (March 2026); NVIDIA partnership for physical AI and robotics cloud |
| Data Sovereignty | US-centric; limited options for EU data residency | Strong European presence; sovereignty-compliant infrastructure in Finland, France, Iceland, UK |
| Consumption Models | Reserved instances (up to 60% discount), Flex Reservations, Spot, On-Demand | Capacity Blocks, On-Demand, Preemptible ($2.69/GPU/hr for B200), public Capacity API |
| Specialization | Large-scale AI training; frontier model infrastructure | Full-stack AI cloud; training, inference, data labeling, and physical AI |
Detailed Analysis
Scale and Financial Firepower
CoreWeave operates at a fundamentally different scale than Nebius today. With $5.13 billion in 2025 revenue, a $66.8 billion backlog, and roughly 250,000+ GPUs deployed, CoreWeave is the clear leader in raw GPU capacity. The company's pioneering approach to compute capital markets—financing GPU fleets as revenue-generating capital assets—has allowed it to scale faster than almost any infrastructure company in history.
Nebius is earlier in its growth arc but is scaling aggressively. The $17.4 billion Microsoft deal and $3 billion Meta agreement provide substantial revenue visibility, and the $2 billion NVIDIA strategic investment announced in March 2026 signals strong confidence in Nebius's trajectory. With a target of 2.5 GW of contracted power by end of 2026, Nebius is positioning to close the capacity gap significantly over the next two years.
Infrastructure Architecture and Vertical Integration
The two companies take notably different architectural approaches. CoreWeave focuses on delivering best-in-class GPU compute infrastructure—bare-metal instances with high-bandwidth networking optimized for distributed AI training. It partners with ecosystem players like Weights & Biases for higher-level tooling, and its Mission Control platform provides enterprise fleet management.
Nebius pursues deeper vertical integration, designing its own server racks and controlling the stack from data center architecture through managed Kubernetes to application-layer tools. Nebius AI Studio provides inference APIs for open-weight models like DeepSeek, Llama, and Flux without requiring separate NVIDIA licenses. The Toloka division adds human-in-the-loop data labeling—a capability CoreWeave doesn't offer at all. This full-stack approach may appeal to teams that want a more opinionated, batteries-included platform.
Pricing and Cost Efficiency
Nebius holds a significant pricing advantage on comparable hardware. H100 instances run approximately $2.95/GPU/hr on Nebius versus $4.76/GPU/hr on CoreWeave for on-demand pricing—roughly 38% cheaper. Preemptible B200 instances on Nebius start at $2.69/GPU/hr, making it particularly attractive for workloads that can tolerate interruption. CoreWeave counters with up to 60% discounts on reserved instances and its new Flex Reservations model introduced in March 2026, which can narrow the gap for committed workloads.
For organizations running large-scale training jobs with predictable capacity needs, CoreWeave's reserved pricing becomes more competitive. But for teams experimenting, running inference, or seeking burst capacity, Nebius's lower on-demand and preemptible rates are compelling.
Geographic Reach and Data Sovereignty
Geographic strategy is one of the starkest differentiators. CoreWeave's infrastructure is concentrated in the United States, making it the natural choice for US-based AI labs and enterprises. Nebius, with data centers across Finland, Iceland, France, the UK, and expanding US presence in New Jersey and Kansas City, offers genuine geographic diversity.
For European organizations subject to GDPR and emerging AI regulations, Nebius provides sovereignty-compliant infrastructure that CoreWeave simply cannot match today. As AI regulation tightens globally, the ability to keep data and compute within jurisdictional boundaries becomes increasingly valuable. Nebius's European roots give it a structural advantage in this dimension.
AI Lab Ecosystem and Enterprise Adoption
CoreWeave has become essential infrastructure for frontier AI development. Its customer roster includes OpenAI, IBM, and other major AI labs training the largest models. This ecosystem creates a flywheel: the most demanding AI workloads drive CoreWeave to optimize its infrastructure, which in turn attracts more frontier customers. CoreWeave's Mission Control platform, with features like GPU Straggler Detection and Telemetry Relay, reflects the operational maturity that comes from serving the most sophisticated AI infrastructure consumers.
Nebius's hyperscaler deals with Microsoft and Meta position it differently—as infrastructure-behind-the-infrastructure rather than a direct platform for AI startups. However, Nebius AI Studio and its managed services stack make it increasingly accessible to mid-market AI teams and enterprises that want a more managed experience than CoreWeave's infrastructure-focused approach.
Next-Generation Hardware and Roadmap
Both companies are racing to deploy NVIDIA's latest silicon. CoreWeave has announced HGX B300 availability and plans to be among the first to deploy Vera Rubin NVL72 in H2 2026. Nebius's AI Cloud 3.1 release brought Blackwell Ultra compute, and its March 2026 NVIDIA partnership specifically targets physical AI and robotics workloads—a forward-looking bet on embodied AI use cases that extends beyond pure LLM training.
The NVIDIA investment in Nebius is notable: it suggests NVIDIA views Nebius as a strategically important distribution channel for its hardware, particularly in markets outside the US. Both companies will have access to top-tier NVIDIA hardware, but their deployment timelines and optimization priorities will differ based on their respective customer bases.
Best For
Training Frontier LLMs (100B+ Parameters)
CoreWeaveCoreWeave's massive GPU fleet, proven track record with OpenAI and other frontier labs, and optimized high-bandwidth networking for distributed training make it the clear choice for the largest training runs. Its scale simply cannot be matched by Nebius today.
Cost-Sensitive AI Inference at Scale
NebiusNebius's significantly lower on-demand pricing ($2.95 vs $4.76/hr for H100) and preemptible instances at $2.69/hr for B200 GPUs make it substantially more economical for inference workloads where cost-per-token matters most.
European AI Operations (GDPR/Sovereignty)
NebiusWith data centers across Finland, Iceland, France, and the UK, Nebius is the only viable choice for organizations requiring European data residency and sovereignty-compliant AI infrastructure. CoreWeave has no European presence.
Full-Stack AI Development Platform
NebiusNebius AI Studio, managed Kubernetes, Toloka data labeling, and integrated inference APIs provide a batteries-included experience. CoreWeave requires assembling more of the stack yourself or through partners.
Enterprise GPU Fleet Management
CoreWeaveCoreWeave's Mission Control platform with GPU Straggler Detection, Telemetry Relay, and enterprise-grade fleet lifecycle management is more mature for organizations operating large dedicated GPU clusters.
Robotics and Physical AI
NebiusNebius's March 2026 partnership with NVIDIA specifically targets robotics and physical AI, combining RTX PRO 6000 GPUs, high-throughput object storage, and integrated data management tailored for embodied AI workloads.
AI Startup Needing Burst GPU Capacity
TieBoth offer flexible consumption. CoreWeave's new Flex Reservations and Spot instances compete well with Nebius's Capacity Blocks and preemptible pricing. The best choice depends on geography and whether you need managed services.
Reserved Long-Term Training Contracts
CoreWeaveCoreWeave's up to 60% reserved discounts, $66.8B backlog proving contract reliability, and unmatched scale make it the safer bet for multi-year, large-capacity commitments for AI training infrastructure.
The Bottom Line
CoreWeave and Nebius are both exceptional GPU cloud providers, but they serve different segments of the market. CoreWeave is the incumbent neocloud leader—the company you choose when you need the largest GPU clusters, the most proven infrastructure for frontier model training, and the confidence that comes with a $66.8 billion backlog and $5+ billion in annual revenue. If you're training models at the scale of GPT-class systems or need massive reserved capacity in the United States, CoreWeave is the default choice.
Nebius is the more interesting strategic play for many organizations. Its pricing is significantly lower, its full-stack approach reduces integration complexity, and its European infrastructure solves a data sovereignty problem that CoreWeave cannot address. The $2 billion NVIDIA investment and hyperscaler deals with Microsoft and Meta validate Nebius's trajectory, and its vertical integration—from custom server racks to AI Studio inference APIs to Toloka data labeling—creates a more complete platform for teams that want managed AI infrastructure rather than bare GPU compute.
Our recommendation: choose CoreWeave for raw scale and frontier training workloads, especially if you're US-based and need the largest possible GPU clusters. Choose Nebius if you prioritize cost efficiency, need European data residency, want a more managed full-stack experience, or are building in emerging areas like physical AI and robotics. For many mid-market AI companies, Nebius's combination of competitive pricing, managed services, and geographic flexibility will deliver better value. But for the biggest training runs powering the next generation of large language models, CoreWeave remains the infrastructure provider of record.