CoreWeave Delivers Leading Inference Performance in MLPerf® Benchmark

CoreWeave, Inc. , The Essential Cloud for AI™, announced landmark results in the MLPerf® Inference v6.0 benchmark suite. Participating in the Datacenter Closed division, CoreWeave leveraged NVIDIA’s newest AI infrastructure, the NVIDIA GB200 NVL72 and NVIDIA GB300 NVL72.

Also Read: AiThority Interview with Glenn Jocher, Founder & CEO, Ultralytics

The AI industry is undergoing a fundamental shift with inference as the new critical focus. As enterprises move AI from experimentation into production and agentic workloads become the new standard, inference has emerged as the critical measure of performance. At the same time, demand for inference is growing faster than the underlying hardware can be deployed, and the gap between theoretical system performance and real-world output has emerged as a defining constraint on how quickly AI companies can grow. CoreWeave’s MLPerf v6.0 results reflect the company’s continued investment in full-stack optimization, consistently turning cutting-edge hardware into real-world inference performance.

“Inference is the defining layer in AI. It’s where models are actually put to work and where performance in production shows up. Benchmarks like MLPerf help measure how theoretical performance translates into real-world output,” said Peter Salanki, co-founder and chief technology officer of CoreWeave. “These latest results reflect our ability to deliver exceptional performance for the most demanding frontier reasoning models at scale through full-stack optimization. That’s why customers rely on CoreWeave to launch, scale, and operate AI workloads in production, where real-world value is created and where it matters most.”

CoreWeave’s v6.0 submissions reflected NVIDIA’s reference configurations as a verified, production-ready baseline across two of the most demanding reasoning models available: DeepSeek-R1 and GPT-OSS-120B. Key results include:

• Continued NVIDIA GB200 NVL72 Leadership: Led performance for DeepSeek-R1 in server and offline mode in tokens per second per GPU¹. The configuration of GB200 NVL72 demonstrated standout throughput on DeepSeek-R1’s sparse Mixture-of-Experts architecture, where efficient serving requires dynamic expert routing and high-bandwidth internode communication.
• NVIDIA GB300 NVL72 Portfolio Leadership: Delivered high server throughput measured in tokens per second per GPU and per-GPU efficiency in the portfolio on DeepSeek-R1, 2X CoreWeave’s own MLPerf® 5.1 results on the same hardware footprint².
• Innovation at Speed: Today, eight of the leading 10 model providers rely on CoreWeave Cloud, enabling customers to innovate at speed.

“The gap between benchmark performance and production reality has been one of the most persistent challenges in AI,” said Nick Patience, vice president & practice lead, AI platforms at Futurum Research. “CoreWeave’s MLPerf v6.0 results, particularly on DeepSeek-R1, demonstrate the company is closing that gap through disciplined, full-stack optimization, which is exactly what enterprises and AI labs need as inference workloads move from experimental to mission-critical.”

CoreWeave’s MLPerf v6.0 results provide additional validation as the only AI cloud to earn top Platinum ranking in both SemiAnalysis ClusterMAX™ 1.0 and 2.0, which evaluate AI cloud performance, efficiency and reliability. These benchmark results reflect CoreWeave’s platform strategy: delivering infrastructure purpose-built for the demands of production AI, from high-performance compute through the software layer that builders depend on to develop, test, and deploy at scale.

Also Read: ​​The Infrastructure War Behind the AI Boom

[To share your insights with us, please write to psen@itechseries.com]