Arm Holdings vs NVIDIA
Relationship
Arm CSS for Mobile 2 and NVIDIA Blackwell do comparable work on accelerator silicon; larger scale (public).
Assembled from the recorded fields for this pair, not hand-checked. The comparison below is read from each company’s own profile.
5 of 6 capabilities — Shares AI compute hardware, accelerator silicon, autonomous driving and 2 more.
Ludbee capability tags · from the product recordsShared product type — Both ship hardware.
Ludbee product recordsLarger scale — NVIDIA: $5.1T market cap, against Arm Holdings's $282.8B market cap.
Ludbee scale figures · valuation, market cap or revenue estimateAligned comparison
Capability overlap
Shared · 5
Not verified for NVIDIA · 1
Recorded for Arm Holdings. NVIDIA’s product records say nothing either way — a missing record is not a missing capability.
Not verified for Arm Holdings · 21
Recorded for NVIDIA. Arm Holdings’s product records say nothing either way — a missing record is not a missing capability.
Products, side by side
Algorithmic pairing — assembled from recorded fields, not hand-checked
Arm Holdings
Hardware
Arm's first self-designed, TSMC-manufactured production CPU — up to 136 Neoverse V3 cores on 3nm — built for sustained agentic-AI data-centre workloads and co-developed with lead customer Meta.
Arm's second-generation mobile compute subsystem — the C2 CPU cluster (C2-Ultra, C2-Pro) with SME2 for on-device agentic AI — positioned by Arm against "the previous generation Arm (Lumex) reference platform".
A licensable microNPU IP core that adds on-device ML inference to area- and power-constrained embedded and IoT designs paired with Cortex-M processors.
A licensable microNPU IP core delivering roughly double the on-device inference performance of Ethos-U55, for Cortex-A, Cortex-R and Neoverse-based edge systems.
Neural processing unit designs licensed to chip makers for running models on edge and mobile devices.
Arm's AI-first mobile Compute Subsystem, a licensable CPU, GPU and system-IP bundle for on-device generative AI, shipping in the vivo X300 and OPPO Find X9.
CPU designs licensed to chip makers for servers and data-centre silicon, including the host processors in AI systems.
A configurable, pre-validated compute subsystem built on Neoverse N4 cores (8–128 cores per die, Armv9.3, up to 3.8 GHz on 3 nm) with integrated system IP, delivered to partners as RTL for agentic-infrastructure silicon.
A licensable physical-AI Compute Subsystem combining Cortex-A and Cortex-R processors with system IP for safety-relevant AI-defined vehicle and robotics SoCs.
NVIDIA
Hardware
Data-centre GPU architecture used for training and serving large models, sold in servers and rack systems.
Data-processing-unit (DPU) platform combining compute with accelerated networking, storage and security for AI-factory infrastructure.
Free application that enhances livestreams and video calls with AI noise removal, background replacement and other audio/video effects; requires a GeForce RTX GPU.
Desktop AI supercomputer powered by the GB10 Grace Blackwell Superchip for local autonomous agents, running models up to 200B parameters for inference.
Deskside AI supercomputer powered by the GB300 Grace Blackwell Ultra Superchip, up to 20 petaFLOPS and 748GB coherent memory, supporting models up to 1T parameters.
Reference baseboard specification (HGX B200, B300, Vera Rubin NVL8) that system integrators and OEMs build into complete AI servers, listed in NVIDIA's Qualified System Catalog.
Edge-AI developer kits (IGX Thor, IGX Thor Mini, IGX Orin) for industrial and medical edge computing.
Family of embedded AI modules and developer kits for robotics and edge AI (Thor, AGX Orin, Orin NX/Nano, Xavier, TX2/Nano series).
Scalable data-centre server systems (e.g. OVX L40S with four or eight GPUs) for AI and graphics workloads, built by NVIDIA OVX partners.
Quantum-X800 InfiniBand switching for large-scale AI clusters, part of NVIDIA's InfiniBand networking line.
Professional GPU line (RTX PRO 2000 through RTX PRO 6000) for AI, graphics and simulation workloads across Blackwell, Ada Lovelace, Ampere and Turing architectures.
Ethernet networking platform (switches, ConnectX SuperNICs, BlueField DPUs, LinkX cables) purpose-built for generative-AI-scale data centres.
NVIDIA's data-centre platform succeeding Blackwell, pairing Rubin GPUs with Vera CPUs at rack scale for agentic AI and reasoning workloads.
Software that virtualizes GPUs across VMs in enterprise data centres and cloud deployments, licensed through NVIDIA's vGPU License and Support Portal.
No counterpart
NVIDIA sells these in a stack layer with no product recorded for Arm Holdings yet — nothing on the other side to compare them against.
Platform
Programming toolkit and libraries for running general-purpose computation on NVIDIA GPUs.
Suite of AI technologies (speech, intelligence, animation models and plugins) for building conversational, actionable in-game characters, mostly MIT-licensed with some components under NVIDIA's open model license.
Supported software suite for building and deploying AI workloads on NVIDIA hardware.
Free development-environment manager for creating, customizing and collaborating on AI applications across GPU systems, with enterprise support available through an NVIDIA AI Enterprise license.
Development platform for AI-driven biology and drug discovery: open models, libraries, datasets and NIM microservices for the full AI lifecycle in biopharma.
End-to-end autonomous-vehicle platform spanning training infrastructure, simulation and safety-certified in-vehicle compute for production autonomy from L2++ to L4.
Open-source model-deployment server for TensorRT, PyTorch, ONNX, OpenVINO and other frameworks across GPUs and CPUs, with production support and stable APIs through NVIDIA AI Enterprise.
Open robotics development platform combining simulation, CUDA-accelerated perception libraries, ROS 2 integration and humanoid tooling for building AI-powered robots.
Suite of libraries and microservices covering the AI agent lifecycle - data curation, customisation, evaluation, guardrails and monitoring.
Platform of OpenUSD-based libraries and microservices for building simulation-ready digital twins and synthetic-data environments used to train and validate physical AI and robots.
Suite of open-source, GPU-accelerated data-science libraries (cuDF, cuML, cuGraph, cuxfilter), rebranding to "CUDA-X for Data Science."
Deployable speech-AI library (ASR/TTS) for production inference, free to prototype via build.nvidia.com and licensed for production deployment through NVIDIA AI Enterprise.
Ecosystem of compilers, runtimes and optimization tools for high-performance deep-learning inference; TensorRT-LLM and Model Optimizer are free on GitHub, with commercial deployment options via NVIDIA AI Enterprise.
Infrastructure service
NVIDIA's AI cloud of GPU clusters and managed AI services, which NVIDIA's own page now presents as its internal environment for building its models, and which is still sold on Microsoft's Azure marketplace.
Model API
Prebuilt inference microservices that package foundation models with optimised serving engines and standard APIs, deployable as hosted endpoints or self-hosted containers.