CRWV Share Price Performance

US$117.95

-65.63 (-35.75%)

US$133.13

Fair Value

US$117.95

-65.63 (-35.75%)

11.4% undervalued

US$133.13

Fair Value

US$117.95

US$133.13

US$70.00

US$53.68

Wed, 3 Dec 25

Fair ValueUS$133.13

Share Pricen/a

CRWV Community Narratives

AnalystConsensusTarget's

Fair Value

Fair Value US$133.13 11.4% undervalued

Market Share Expansion Will Drive Sustained Gains From Accelerating AI Adoption

WIn2026's

Fair Value

Fair Value US$70 68.5% overvalued

Deep Dive: Assessing the Sustainability of CRWV’s Compute-as-a-Service Model

AnalystLowTarget's

Fair Value

Fair Value US$53.68 119.7% overvalued

AI Infrastructure Expansion And Leverage Will Drive Utilization And Margin Risks Ahead

About CRWV

Founded: 2017
Employees: 2189
CEO: Michael Intrator
WebsiteView website: www.coreweave.com

CoreWeave, Inc. operates as a cloud infrastructure technology company in the United States. The company offers CoreWeave Cloud platform that comprises proprietary software and cloud services that deliver the automation and efficiency needed to manage complex artificial intelligence (AI) infrastructure at scale. It also offers data and storage solutions, such as Local Object Transport Accelerator; infrastructure control solutions, including CoreWeave Kubernetes service; mission control services, including node, rack, and fleet lifecycle management; model and agent development tools comprising Weights & Biases, an AI developer platform; and runtime acceleration. In addition, the company offers graphics processing unit compute, CPU compute, networking services, managed services, and virtual and bare metal servers. Its services also include visual effects rendering, machine learning, pixel streaming, and batch processing. The company was formerly known as Atlantic Crypto Corporation and changed its name to CoreWeave, Inc. in December 2019. CoreWeave, Inc. was incorporated in 2017 and is based in Livingston, New Jersey.

Recent CRWV News & Updates

Announcement • Jun 18

CoreWeave Sets New AI Training Records In MLPerf Training v6.0 And Trains DeepSeek-V3 In Approximately Two Minutes

CoreWeave, Inc. announced record-breaking results in the MLPerf Training v6.0 benchmark suite. Running on the same CoreWeave Cloud infrastructure available to customers, CoreWeave delivered the fastest DeepSeek-V3 671B training performance in the benchmark, training one of the most computationally demanding models ever benchmarked in 2.02 minutes on 8,192 NVIDIA GB300 NVL72 GPUs — the largest GB300 cluster submitted in this round. CoreWeave submitted three GB300 NVL72 configurations on DeepSeek-V3 671B, the benchmark's most demanding workload, achieving the fastest results across all Closed/Available-cloud submissions. On 8,192 GPUs across 2,048 nodes, CoreWeave hit target quality in approximately two minutes. Scaling down to 4,096 GPUs across 1,024 nodes, training was completed in 3.09 minutes. At 2,048 GPUs across 512 nodes, the result was 5.54 minutes. As the cluster size doubled at each step, training time improved predictably — a consistent, near-linear scaling efficiency that reflects full-stack optimization across every layer of the CoreWeave platform. CoreWeave was the only submitter in the v6.0 round to scale a GB300 platform beyond 2,048 GPUs on DeepSeek-V3. The scaling story is as significant as the result demonstrating that full-stack optimization delivers more usable performance per GPU than raw scale alone. For AI teams operating under compute budgets, that scaling curve translates directly into faster training runs, shorter development cycles, and quicker time to production. CoreWeave's MLPerf Training v6.0 results demonstrate that full-stack infrastructure advantages extend across deployment sizes, not just at frontier scale. On NVIDIA GB300 NVL72, CoreWeave's 4,096-GPU deployment reached the Llama-3.1-405B reference quality target in 9.77 minutes, achieving near-parity with larger GB200 deployments while using 20% fewer GPUs. The run was built on NVIDIA NeMo Framework Release 26.04, with full CUDA graphs, Tensor/pipeline/context-parallel sharding tailored to the GB300 NVL72 topology, and NVIDIA Spectrum-X Ethernet running RoCE for scale-out fabric. On a compact 8-node, 64-GPU NVIDIA HGX B200 cluster connected via InfiniBand, CoreWeave trained GPT-OSS-20B in 26.98 minutes and Llama-3.1-8B in 16.54 minutes. Through optimizations in orchestration, communication libraries, and distributed training configuration, CoreWeave delivered performance from the B200 platform that rivals larger and newer-generation deployments. This validated that CoreWeave's engineering advantages benefit customers at every scale, not just the largest clusters. CoreWeave's MLPerf Training v6.0 results reflect optimizations across every layer of the stack: Fleet-Wide Performance Consistency: CoreWeave Mission ControlTM continuously performs health checks across the latest rack scale systems like GB300, validating hardware, firmware, network, and thermal health before and during large-scale training jobs. This reduces stragglers and ensures workloads run on a consistent, performance-qualified infrastructure baseline. NVLink-Domain-Aware Scheduling: CoreWeave SUNK is topology-aware by design, intelligently placing workloads to maximize locality and co-locating expert-parallel groups within the same NVL72 domain to minimize inter-rack communication for MoE workloads. Optimized Network Performance: CoreWeave employs a rail-aware networking strategy that balances traffic, ensuring bandwidth is utilized efficiently and preventing hotspots from developing within the fabric at multi-thousand-GPU scale. CoreWeave's MLPerf Training v6.0 results were achieved on the same production infrastructure available to customers. The networking fabric, scheduler, storage architecture, and CoreWeave Mission Control orchestration platform used in MLPerf are the same systems customers use to run real-world workloads. This was not a benchmark-only environment, it was a validation of the platform customers can access.

Recent updates

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CoreWeave, Inc. Stock Price

CRWV Share Price Performance

CRWV Community Narratives

Market Share Expansion Will Drive Sustained Gains From Accelerating AI Adoption

Deep Dive: Assessing the Sustainability of CRWV’s Compute-as-a-Service Model

AI Infrastructure Expansion And Leverage Will Drive Utilization And Margin Risks Ahead

Deep Dive: Assessing the Sustainability of CRWV’s Compute-as-a-Service Model

AI Infrastructure Capacity Leadership Will Drive Massive Long Term Earnings Power

AI Infrastructure Expansion And Leverage Will Drive Utilization And Margin Risks Ahead

Market Share Expansion Will Drive Sustained Gains From Accelerating AI Adoption

Trending Discussion

Recently Updated Narratives

Deep Dive: Assessing the Sustainability of CRWV’s Compute-as-a-Service Model

AI Infrastructure Capacity Leadership Will Drive Massive Long Term Earnings Power

AI Infrastructure Expansion And Leverage Will Drive Utilization And Margin Risks Ahead

Snowflake Analysis

CoreWeave, Inc. Key Details

About CRWV

Recent CRWV News & Updates

CoreWeave Sets New AI Training Records In MLPerf Training v6.0 And Trains DeepSeek-V3 In Approximately Two Minutes

CoreWeave Stock Draws Attention With Record AI Growth Surge and Heavy Debt Expansion

CoreWeave: The Liabilities Keep On Piling Up

Recent updates

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