Intel has published new benchmarks of its Project Battlematrix workstation with Arc Pro B60 GPUs in MLPerf v5.1.
Intel Project Battlematrix With Arc Pro B60 GPUs & Xeon 6 CPUs Achieves Up To 4x Higher Perf/$ Versus NVIDIA L40S & 25% Uplift Versus RTX PRO 6000 In MLPerf v5.1 Benchmarks
Press Release: Today, MLCommons released its latest MLPerf Inference v5.1 benchmarks, showcasing results across 6 key benchmarks for Intel’s GPU Systems featuring Intel Xeon with P-cores and Intel Arc Pro B60 graphics, inference workstations code-named Project Battlematrix.
In Llama 8B, Intel Arc Pro B60 performance per dollar advantages of up to 1.25x and up to 4x compared to NVIDIA RTX Pro 6000 and L40S, respectively. The results underscore the performance and accessibility of an all-Intel platform that addresses emerging AI inference workloads across high-end workstations and edge applications.
[Editor's Note] In llama 3.1 (8b Datacenter) inference workloads, the Intel Arc Pro B60 "Project Battlematrix" solution generates 6472.37 Samples/s in offline and 5348.45 Queries/s versus 1642.22 samples/s and 1207.14 Queries/s on the NVIDIA L40S. The RTX PRO 6000 "Blackwell" GPU is much faster but then comes the cost factor where Intel says its providing 25% better perf/$.[End]
Why It Matters: Until now, limited options existed for professionals who prioritized platforms capable of delivering high inference performance without compromising data privacy or incurring heavy subscription costs tied to proprietary AI models, but required capabilities to deploy large language models (LLMs).
These new Intel GPU Systems, code-named Project Battlematrix, are designed to meet the needs of modern AI inference and provide an all-in-one inference platform combining full-stack validated hardware and software.
Intel GPU systems aim to simplify the adoption and ease of use with a new containerized solution built for Linux environments, optimized to deliver incredible inference performance with multi-GPU scaling and PCIe P2P data transfers, and designed to include enterprise-class reliability and manageability features such as ECC, SRIOV, telemetry, and remote firmware updates.
CPUs continue to play a vital role in AI systems. As the orchestration hub, the CPU handles preprocessing, transmission, and overall system coordination. Intel sustained improvements in CPU-based AI performance over the past four years have established Intel Xeon as the preferred CPU for hosting and managing AI workloads in GPU-powered systems.
Intel also remains the only vendor submitting server CPU results to MLPerf, demonstrating leadership and a deep commitment to accelerating AI inference capabilities across both compute and accelerator architectures. Notably, Intel Xeon 6 with P-cores achieved 1.9x performance improvement gen-over-gen in MLPerf Inference v5.1
About the author: A Software Engineer by training and a PC enthusiast by passion, Hassan Mujtaba serves as Wccftech's Senior Editor for hardware section. With years of experience in the industry, he specializes in deep-dive technical analysis of next-generation CPU and GPU architectures, motherboards, and cooling solutions. His work involves not only breaking news on upcoming technologies but also extensive hands-on reviews and benchmarking.
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